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SynPlan

December 4

2009

Lilien Cheminformatics, revolutionizing pharmaceutical development

Includes: 3
-
page Executive Summary (not including diagrams), Final Business Model
Canvas, Appendices
including Competition Analysis, Market Analysis, Business Case, Marketing Strategy, Sales and Marketing
Plan, Development Plan, Staffing Plan, Operations Model, Financial Model, Financing Plan, Customer
Interviews, Expert Interviews


Dejana Bajic, Brian Keng, Amanda Manarin, Maria Safi & Peter Park

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2

Table of Contents


E
XECUTIVE
S
UMMARY

DESCRIPTION

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4

VALUE PROPOSITION

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4

CUSTOMER SEG
MENTS

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5

Table 1.1: Brief summary of R&D spending in 2008 2

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5

MAJOR COMPETITORS

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5

ARC
HEM BY
S
IMBIOSYS

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5

T
HERESA BY

M
OLECULAR
-
N
ETWORKS

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6

BARRIERS TO ENTRY

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6

FINANCIAL ESTIMATION
S

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6

COSTS & REVENUE STRU
CTURE IN NEXT 5 YEAR
S

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..

6

BUSINESS MODEL CANVA
S

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7

COMP
ETITION ANALYSIS

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8

1

D
IRECT
C
OMPETITORS

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8

1.1 ARChem

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8

1.2 Theresa

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8

2

I
NDIRECT
C
OMPETI
TORS
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9

2.1 LHASA

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9

2.2 Synchem Inc.

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10

3

O
UT
-
OF
-
CATEGORY COMPETITORS

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10

3.1 SciFinder

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10

3.2 Beilstein
Crossfire/Reaxsys

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11

4

D
ISCUSSION
/

S
TATUS
Q
UO

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11

MARKET ANALYSIS

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12

Top 15 US Pharmaceutical Company Expenses Compared:

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13

Brief summary of R&D spending in 2008 :

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13

Addressable Market:

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14

BUSINESS CASE

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14

Scenario 1: Successful
drug development (delivered to market)

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14

Scenario 2: Unsuccessful drug development (fails during clinical trials)

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15

Scenario 3: Reverse Engineer Competitor Drug

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15

T
YPICAL
T
OTAL
S
AVINGS PER
Y
EAR
:

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.

15

P
RICING
J
USTIFICATION

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16

MARKETING STRATEGY &

PLAN

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SALES PLAN

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19

DEVELOPMENT PLAN

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19

Detailed Milestone Descriptions

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20

Detailed Release Descriptions and Goals

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21

STAFFING PLAN

* SEE SPREADSHEET FO
R DETAILS

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22

OPERATIONS MODEL

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22

O
PERATIONS
P
LAN
O
UTLINE

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24

FINANCIAL MODEL

* SEE SPREADSHEET FO
R DETAILS

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25

5

Y
E
AR
P
RO
F
ORMA
I
NCOME
S
TATEMENT

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25

5

Y
EAR
P
RO
F
ORMA
C
ASH
F
LOW

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26

FINANCING PLAN

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27

Round 1


Jan
Year 1 (Seed Funding)

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27

Round 2
-

Jan Year 2 (VC Part I)

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27

Round 3
-

Jun Year 2 (VC Part II)

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27

Exit Scenario 1


Dec Year 5 (Acquisition by private equity)

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27

Exit Scenario 2


Dec Year 5 (IPO)

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27

CUSTOMER INTERVIEWS

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28

D
AVID
D
UBINS
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28

G
RACE
N
G
(M
EDICINAL
C
HEMIST
)

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29

A
NDREW
C
OOPER

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30

N
OTES

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30

EXPERT INTERVIEWS

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31

M
ALCOLM
B
ERSOHN

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31

A
BRAHAM
H
EIFETS

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31

IP STRATEGY

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32

T
RADE
S
ECRETS
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32

C
OPYRIGHTS

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33

T
RADEMARKS

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Executive Summary

Description

SynPlan is a
computer
-
aided organic synthesis tool that automates the complex and time
-
consuming
process of finding a series of chemical reactions to manufacture an organic compound at an industrial
scale. It leverages recent advances in artificial intelligence and co
mputing power to speed up this key
step in the drug development cycle, positioning itself as an essential tool in the process chemist’s tool
box.

Today, generating these reactions involves using pen and paper to draw a series of complex organic
reactions a
ided only by his/her intuition of what is likely to be a valid step. With over 100 million
chemical substances and sequences
1
, it is clear that traditional methods are inadequate to cope with the
growing needs of modern pharmaceutical development. SynPlan

will augment the chemist’s intimate
knowledge of the field by providing a list of possible solutions to the problem and allowing the final
judgement to be decided by a human expert, automating away the tedious task of finding valid solutions
to the proble
m.

SynPlan will be distributed to customers on site by an expert application engineer that will initially train
and showcase the benefits of using our product to the customer’s chemists. Support by these expert
engineers will be given to each customer to
ensure that they are using the tool to maximize their cost
savings, productivity and drug development.

Value proposition

Once a pharmaceutical company acquires a patent on a new drug, cheaper generic versions of the drug
cannot be sold until the patent ex
pires. Therefore each pharmaceutical company wishes to decrease the
drug development time to extend the period in which they can sell the drug exclusively on the market.
One of the most time
-
consuming processes in drug development cycle is finding a valid
series of
chemical reactions to generate the desired compound for industrial scale production. This process can
take up to three years which translates directly to time that can be used to sell the drug. SynPlan will
automate this task reducing this three
year task to three months. This savings in production time
translates directly into decreased labour costs and increased revenue from a larger period of time to sell
the drug exclusively on the market.




1

Chemical Abstracts Service, http://www.cas.org/newsevents/connections/heterocycle.html

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An added bonus comes when a competitor product is nee
ded to generate an alternative, marketable
drug. In such a situation, in house scale up can be performed for a competitor compound using a
completely novel synthesis so the newer analog is patentable.

Customer Segments

Lilien Cheminformatics plans to targ
et the pharmaceutical industry because it has the greatest need for
automating this synthesis process. The customer segments will be broken down into two segments
based on the size of the companies:

a) Large pharmaceutical companies (estimated 500+ licen
ses/year)

b) Small to mid
-
sized pharmaceutical companies (up to 500 licenses/year)

Lilien Cheminformatics will concentrate primarily on two markets USA and Europe because these two
regions represent the largest portion of global pharmaceutical sales (40.3%

US, 32% Europe)

2
. Lilien
Cheminformatics will initially focus product development towards the targeting the large
pharmaceutical customer segment due to their purchasing power noted in Table 1.1.

Table 1.1: Brief summary of R&D spending in 2008 2

US$ sp
ent (millions)

# Pharmaceutical companies in range

100
-
500

17

500
-
1000

8

1000+

14

Major Competitors

Theresa and ARChem are two products which fall under the direct competitors’ category for SynPlan.
The comparison of SynPlan with ARchem and Theresa is provided below.

ARChem by Simbiosys

ARChem is a computer
-
aided organic synthesis tool from Simbiosys.
While it provides similar
functionality to SynPlan, it is limited technical capabilities make it impractical for wide
-
spread industrial
use. While the average number of reactions to generate a drug is 8.1
3
, ARChem is limited to an average
length of 3 rend
ering it unnecessary in most applications. In addition, it does not provide full support
for stereo
-
chemistry, a key consideration in creating any organic compound. SynPlan will not have these
technical limitations and will provide 8 steps during our bet
a and scale up to 12 for the first release.




2

Pharmaceutical Executive, May2009, Vol. 29 Issue 5, p68
-
79, 8p; (AN 40126374)

3

Carey et. al, “Analysis of the reactions used for the preparation of drug candidate molecules”, The Royal Society of
Chemistry, 2006.

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Theresa by Molecular
-
Networks

Theresa is another computer
-
aided organic synthesis tool from Molecular
-
Networks. Theresa does not
provide completely automation of this process; instead, it provides the process
chemist with an
interactive search still leaving the bulk of the work to be done by the chemist. Furthermore, Theresa
uses a set of theoretical reaction rules which may not work in practice as opposed to reaction rules with
a historical precedent used by
SynPlan.

Barriers to Entry

T
he primary barriers to entry relate to our superior domain knowledge and technical expertise. Our
domain knowledge and partnerships places a significant barrier to entry because knowledge of
retrosynthetic chemistry combined wi
th algorithms is only known to very specialized researchers and
practitioners in the field. Partnerships with University of Toronto’s Computational Biology lab as well as
other experts in the field, put us ahead of new entrants into the market. Beyond ou
r domain
knowledge, Lilien Cheminformatics also possesses proprietary search and planning algorithms
developed at our lab which surpass existing competitors’ technology in the field while simultaneously
providing a large barrier to any new entrant into th
e market space. With Lilien Cheminformatics’
combined expertise in chemistry, medicine and computer science, it sits at a distinct advantage over
new entrants into the market as well as existing competitors.

Financial Estimations



First set of customers
are the initial 200 beta testers. ($40k license + $10k support = $10m revenue)



Increase in fame through advertisement and word of mouth brings in more customers by year 4.



Small and large pharmaceuticals will require our product in order to keep their edge

in R&D by year
5, creating large and fast sales



Number of support crew rise with increase in rise of customers



All employment salaries are based on 60k/year model

Costs & Revenue Structure in Next 5 Years

All figures are in thousands

Year 1

Year 2

Year 3

Year 4

Year 5

Revenues












Licenses


$
-



$
-



$ 14,160


$ 77,520


$ 414,640


Support Handling


$
-



$
-



$
-



$
-



$
-




Setup Charge


$
-



$
-



$ 177


$ 792


$ 4,214


Training & Support


$
-



$
-



$ 3,540


$ 19,380


$ 103,660


Total Support


$
-



$
-



$ 3,717


$ 20,172


$ 107,874

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Total Revenue


$
-



$
-



$ 17,877


$ 97,692


$ 522,514









Expenses












General &
Admin


$ 331


$ 347


$ 593


$ 592


$ 592


Product Dev.


$ 398


$ 463


$ 612


$ 632


$ 1,165


Sales & Marketing


$ 230


$ 555


$ 885


$ 1,005


$ 1,005


Support


$ 109


$ 278


$ 986


$ 2,638


$ 5,234


Total Operating Costs


$ 1,068


$ 1,644


$ 3,077


$ 4,868


$ 7,997









Net Earnings Before Taxes


$ (1,068)


$ (1,644)


$ 14,800


$ 92,824


$ 514,517


Taxes (Assume 20%)


$
-



$
-



$ 3,101


$ 18,565


$ 102,903

Net Earnings


$ (1,068)


$ (1,644)


$ 11,699


$ 74,259


$ 411,614



Business Model Canvas


Leave me blank.




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8


Appendicies

Competition Analysis

The competition analysis for
SynPlan

is presented below. ARChem and Theresa are the

only direct
competing products, whereas the most threatening competitors have been described in the indirect and
out
-
of
-
category sections. Company speci
fi
c data, where available,

has been included wit
h each
competitor. Unless specifically

mentioned, the company has no

international o
ff
ices.


1 Direct Competitors

1.1 ARChem

Company:

Simbiosys

Structure:

Private

Company website:

www.simbiosys.ca

Company Size:

10 people

CEO:

Aniko Simon

Partners:

Sun Microsystems, IBM, Accelrys, Elsevier, Alfa Aesar, Lilien Lab at University

of Toronto.

The
partnerships with Sun, IBM and Accelrys are for grid computing and software porting. Elsevier and Alfa
Aesar provide databases (see Indirect Competitors) to be

used by

ARChem. The information about
company size as well as the CEO and company structure

comes from personal knowledge and
interaction of the author with Simbiosys representatives.

Competing Product
-

ARChem:

ARChem is a tool aimed at helping chemists
design

viable synthetic
routes for the target molecules. The tool provides automated extraction of

reaction rules from
reaction databases and performs exhaustive search for synthetic routes.

ARChem does not handle
stereo
-
chemistry and chirality.

Threat Lev
el:

Medium.

ARChem is a Retrosynthetic chemi
cal planner, and is one of the fi
rst of its kind.
However,

the major drawback of this product is its inability to search for synthetic routes longer than

3
steps. However, typical synthetic plans are much longer
than 3 steps. Therefore, the plans

ARChem is
able to generate, are extremely limited in their advantage to the chemist. We

note that, ARChem can
search for longer synthetic plans as well. However, since it uses a

brute
-
force exhaustive search, plans
longer

than 3 steps are infeasible in their run time due

to the combinatorial explosion of the search
space. (For instance, using exhaustive search, a

plan involving 5 steps, with a reaction database size of
5000 reactions, can possibly take up

to 15 years of ru
ntime.)

1.2 Theresa

Company:

Molecular Networks

Type:

Private

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9

Number of Customers:

100
4

CEO:

Prof. Johann Gasteiger

Headquarters:

Leeds, UK.

Website:

http://www.molecular
-
networks.com/

Partners:

Accelrys, biomax, BioSolveIT GmbH, Chemical Computing Group,

Inc., Inte:Ligand,

Optibrium
Limited, Symyx Technologies.

We note that none of the partnerships are in the chemical synthesis domain.

Product Description:

Theresa is a web
-
based tool for stepwise retrosynthetic analysis of

a target
compound. Theresa uses
reaction and publication databases to search for synthetic

plans/routes.
Based on reaction similarity with a previously known synthesis, Theresa can

also suggest novel steps
for a synthesis. However, Theresa does not generate complete, novel

synthetic
routes for previously
unknown targets. Furthermore, it does not handle stereo
-
chemistry and chirality.

Threat Level:

Medium. Theresa is a retrosynthetic planner that allows for search of

reaction databases
and publications. Its major limitations lie in its

inability to generate

novel synthetic plans from scratch
and its reliance on theoretical chemical rules vs. historically precedented chemical reactions. In
addition, it cannot deal with stereochemistry and

chirality.


2 Indirect Competitors

2.1 LHASA

Comp
any:

Harvard University

Type:

Private

CEO:

Dr. E. J. Corey

Headquarters:

Boston, MA.

Website:

http://lhasa.harvard.edu/

Key Partners:

Academia.

Product Description:

LHASA is an acronym for Logi
c and Heuristics Applied to Syn
thetic Analysis. The
program
comes out of E. J. Corey's Lab at Harvard University. LHASA

helps the chemist to interactively
derive synthetic routes from the target molecule to available starting materials. However, LHASA
requires the user to manually create a set of

reaction/chemistry

rules instead of extracting these rules
from chemical reaction databases.

It is worth noting that LHASA does NOT automatically generate
complete synthetic routes,

instead it requires the chemist to select a reaction at each step manually. In
this way, LHA
SA

unfolds the search tree, one step at a time, depending on the user input.


Threat Level:

Low. LHASA, in essence, is a work
fl
ow tool or visual aid. It does not

provide automated
plan generation. As the search tree is unfolded one step at a time, plans

g
enerated by LHASA are
limited by the interacting chemist's knowledge. As the search is

guided by the chemist selecting a
reaction at each step, LHASA cannot generate completely

novel and previously unknown routes/plans.
Furthermore, LHASA does not provide
access

to the vast knowledge databases which are crucial to



4

http://www.molecular
-
networks.com/com
panyprofile

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generate novel and complex synthetic

plans, instead requiring the chemist to generate chemical rules
manually.

2.2 Synchem Inc.

Company:

Synchem Inc.

Type:

Private

Headquarters:

Elk Grove Village,

Illinois.

Key Customers:

Astra Zeneca, Ambit Biosciences, TorreyPine Therapeutics, TetraPhase

Pharmaceuticals,
GSK Research.
5

Website:
http://www.synchem.com

Product Description:

Synchem Inc. specializes in co
ntract research and organic syn
thesis. It pro
vides
services to various companies including pharmaceuticals which can outsource the scale up process to
Synchem. Currently, its c
atalog contains about 1000 prod
ucts/molecules that can be manufactured for
its customers.

Threat Level:

Low. Synchem is a che
mical manufacturing company. It does not provide

automated tools
to help pharmaceutical medicinal chemists in organic synthesis. Instead it

uses its in house chemists to
perform scale up.

3 Out
-
of
-
category competitors

3.1 SciFinder

Company:

American Chemic
al Society

Type:

Private / Non
-
pro
fit.
6

Number of Customers:

154,000
7

CEO:

Madeleine Jacobs
7

Headquarters:

Washington, DC.

Website:

http://www.acs.org

Customer segments:

Researches in academia, researchers in industry, authors, corporate

and
government
research labs.

Product Overview:

SciFinder is a research discovery tool. It provides access to a

nu
mber of publications
in scientifi
c

fi
elds including organic chemistry. It allows the medicinal

chemists to search for previously
published syntheses. However
, it neither allows planning of

a new synthetic route for previously
designed molecules, nor does it create synthetic plans

for novel compounds.

Threat level:

Low. SciFinder is a chemical database. It provides text mining access to a

large number of
previo
usly published chemical syntheses. The company itself aims to publish

chemical papers, hold
conferences in recent chemical advancements as well as maintains

curated databases of chemical
knowledge such as SciFinder vs. producing industrial search

and plann
ing software.




5

http://www.synchem.com/

6

American Chemical Society. (1 October). Hoover's Company Records,57675. Retrieved October 4, 2009, from
Hoover's Company Records. (Document ID: 168282271).

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3.2 Beilstein Cross
fi
re/Reaxsys

Company:

Elsevier

Type:

Public.
7

Number of Customers:

7000
8

CEO:

Ian R. Smith, Mark H. Armour
8

Headquarters:

New York, Amsterdam.
8

9

Website:

http://www.info.cross
fi
redatabases.com, www.elsevier.com

Key
Partners:

Bayer AG, Fujitsu, Boehringer Ingelheim, Informationszentrum, Chemie

Biologie, University
of Bath, Mercachem, Novasep, Vienna University of Technology, Pharmazie ETH Zuerich.

10

Customer segments:

Researches in academia, researchers in industry, a
uthors, corporate

and
government research labs.

Product overview:

Reaxys is a chemical work
fl
ow system. It provides searchable access to reaction and
substance databases to aid synthesis planning. It also provides access

to chemistry publications since
17
71 and patent publications from 1869
-
1980. However, it

neither allows planning of a new synthetic
route for previously designed molecules, nor does

it create synthetic routes for novel compounds.

Threat level:

Low. Reaxsys is a chemical work
fl
ow system. It

provides text mining

access to a large
number of previously published chemical syntheses. The company itself is

a publishing company, with
products ranging from scienti
fi
c journals to scienti
fi
c databases.

4 Discussion / Status Quo

The last decade has see
n a shift towards computer assisted organic synthesis. The vast

deployment of
chemical databases such as Beilstein and SciFinder is a testament to this

paradigm shift. However, the
number of retrosynthetic planning tools which can provide

e
ff
icient and com
plete synthetic plans for
novel

compounds remains small. The fi
rst approaches towards full automation including ARChem and
Theresa, have already seen willing

customers even though their eff
ect
iveness remains questionable
11
.
From our initial customer

intervi
ews, involving repres
entatives from companies like Pfi
zer as well as from
academia, we

gather that the community is very open to a tool which can aid them in generating
previously unseen and complex synthetic routes. We also believe that we also have a sec
ond
-
mover

advantage in this market. Our targeted customers have already been educated about the

potential
usefulness of a retrosynthetic planner by our competitors. Consequently, they are

also much more
cognizant of the extensive limitations of the existin
g solutions. Hence, we

are con
fi
dent that right now is
a ripe time to o
ff
er this community a complete and e
ffi
cient

retrosynthetic planning solution.




7

Elsevier B.V. (1 October). Hoover's Company Records,161041. Retrieved October 4, 2009, from Hoover's Company
Records. (Document ID: 1712299121).

8

Elsevier B.V. (1 October). Hoover's Company Records,161041. Retrieved October 4, 2009, from Hoover's Company

Records. (Document ID: 1712299121).

9

http://www.info.cross_redatabases.com/contact.html

10

http://info.reaxys.com/development partners

11

http://www.simbiosys.ca/blog/2009/02/13/new
-
paper
-
on
-
archem
-
route
-
designer

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12


Figure 1: Magic quadrant competitor analysis. E
ffi
ciency comprises of: the speed of

execution or runtime
of the program, and the amount of user intervention required. Completeness is de
fi
ned b
y reaction
library size, length of suggested plans, as well as size of the

search space considered. Note that to
achieve higher
c
ompleteness; a search algorithm must

only discard areas of search space which do not
fi
t user de
fi
ned criteria. The out of cate
gory

competitors are not included, since they do not generate
plans and hence the Completeness dimension is invalid for them. Also, SynChem represents all chemical
manufacturing

companies, which employ chemists to scale up a target compound.

Market Analysi
s

The m
u
lti
-
billion dollar pharmaceutical industry is facing
a financial
crisis in the near
future
12

for the
following
reasons:

-

The industry will become a target for major cost
-
cutting as the size of the health sector changes in
proportion to the overall

economy.

-

The capacity of the industry to exert pricing power against a consolidating payer base is shrinking fast.

With
growing
mergers and acquisitions
trends, during

the past decade the
pharmaceutical companies
have been using job reductions as one of the cost
-
saving strategies. With average sales of
601K
1

per



12

Looney, William; industry Audit; Pharmace
utical Executive; Sep2009, Vol. 29 Issue 9, p54
-
72, 11p

Efficiency

Completeness

ARChem

Theresa

SynChem

LHASA

SynPlan

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13

employee among the top 27 companies, it do
es not
seem clear how this strategy will
yield increased
productivity per worker employe
d. The record from past mergers suggests that payoff will take years to
accomplish.

Also, considering the expense breakdown as shown below, it is easy to see where most of
the money is being spent.

Top 15 US Pharmaceutical Company Expenses Compared
13
:


% of

expenses

Cost of Goods

29

Marketing and Administrative

30

R&D

15

Other

26


SynPlan will quickly evolve from being a commodity to simply a necessity with the following motivation:

Saving money



Pharmaceutical companies will save anywhere from thousands to tens of millions of
dollars by extending the duration of sales under the patent. Refer to
Business Case analysis
section for
exact figures.

More capabilities


Empowered by fast and reliable a
lgorithms
,

SynPlan is capable of providing solutions
to synthesis problems that are currently not solvable by humans. Our customers will have the ability to
explore new horizons
when it comes to

medical research
.


Pharmaceutical companies gain access to Sy
nPlan by purchasing an annual software license. Depending
on the number of licenses purchased, SynPlan’s customer base is broken down into two segments:

α) Alpha group, major pharmaceutical companies


500+ licenses/year

γ) Gamma group, small to mid
-
sized
pharmaceutical companies


up to 500 licenses/year

Brief summary of

R&D spending in 2008
14
:

US$ spent (millions)

# Pharmaceutical companies in range

100
-
500

17

500
-
1000

8

1000+

14


This summarizes the size of the Alpha customer segment as well.
Lilien
Cheminformatics
’ goal is to gear
the product development towards the Alpha group as they are the biggest possible source of revenue.

Lilien Cheminformatics’ primary focus will be breaking though Canadian Pharmaceutical R&D market.
Canada is at the forefron
t of discovery when it comes to the pharmaceutical sector. Human health
related research in Canada generates 70% of all revenues, and close to 90% of all R&D
15
. Canada ranks
fourth internationally when it comes to health research patents. Over $1.3 billion
was spent on
biopharma
-
related research in Canada in 2007
2
. Canada also has the second highest number of



13

http://www.cptech.org/ip/health/econ/allocation.html

14

Pharmaceutical Executive, May2009, Vol. 29 Issue 5, p68
-
79, 8p; (AN 40126374)

15

http://investincanada.gc.ca/eng/industry
-
sectors/life_sciences/
bio
-
pharma.aspx

L
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14

biotechnology companies in the world
16
. Hence Lilien
Cheminformatics

has an enormous advantage of
being located within the pharmaceutical cluster in Tor
onto.

Addressable Market:



US companies spend $39 billion in 2003 on R&D
17



Assuming that the largest portion of R&D is made up of drug development costs, Lilien
Cheminformatics can reduce costs at all stages of pre
-
clinical direct cost.



Direct preclinical
costs: 121 million / 802 million = 15%
18

Addressable market of big pharma R&D budget
:

= $39 billion on R&D * 15% on direct costs

= $5.9 billion

Business Case

Cost:


User

Notes

SynPlan license

$
4
0,000

Volume (500+) p
er seat yearly license.

IT support

$500

Support for machines servers and licensing setup.

SynPlan support costs

$10,0
00

Application engineer assistance training/support.

Total:

$51,000



Assumptions:



Fully loaded, $250,000/year organic chemist based on salary and benefits, research support
costs, and general company overhead.
19




Assume 8 medicinal
/process

chemists working a drug scale up/initial development
.
20




Estimate of a
verage time saved by SynPlan 6 months vs. manual effort

based on customer
interviews
:

o

1

months savings during initial de
velopment

o

5
months savings during scale up

Scenario 1: Successful drug development (delivered to market)



Time savings for 8 organic chemists, average of 6 months savings: $1,000,000




16

http://investincanada.gc.ca/download/833.pdf

17

http://
www.cbo.gov/doc.cfm?index=7615

18

http://
www.cbo.gov/doc.cfm?index=7615

19

http://
www.jaici.or.jp/sci/
SCIFINDER
/
roi
_1.pdf

20

http://
www.jaici.or.jp/sci/
SCIFINDER
/
roi
_1.pdf

L
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15



6 months more time selling drug under patent protection assuming drug does

1/100
th

as well as
Lipitor
21
, saves $64.5 million dollars


Savings:



Eight licenses over 6 months: $0.2 million



Savings: $64.5 million

+ $1 million



$
0.2 million = $6
5
.3 million

Scenario 2: Unsuccessful drug development (fails during clinical trials)



Time

savings for 8 organic chemists, average of 2 months savings: $333,333



Assume 18 potential drugs in initial stage development ready for clinical
22


Savings:



Eight licenses ove
r 2 months: $68
,000



Savings: $333,333 * 18


$68
,000 = $5.9 million

Scenario
3:
Reverse Engineer Competitor Drug



Promising drug patent that was filed by competitor. Slight modifications might result in an
enhanced version of the drug. Use SynPlan to reverse engineer and modify a competitor’s drug
so that you can beat them to clinica
l trials and FDA approval.



Time savings for 8 organic chemists, average of 6 months savings: $1,000,000



Develop and get FDA approval a
drug under patent protection assuming drug does 1/100
th

as
well as Lipitor
23
21


Savings:



Eight licenses over 6 months: $0.2 million



Savings: $64.5 million

+ $1 million



$
0.2 million = $6
5
.3 million


Typical Total Savings per Year
:
24



Out of
$
802 million cost to develop
drug: preclinical (4.3 years), clinical

/

FDA
(7.5 years)



Direct costs

o

Pre
-
clinical:
$
121 million

o

Clinical:
$
282

million




21

$12.9 billion annual sales, 2008 annual report
http://media.pfizer.com/files/annualreport/2008/annual/review2008.pdf

22

based on average number of drugs in phase 3 pipelin
e

http://media.pfizer.com/files/annualreport/2008/annual/review2008.pdf

23

$12.9 billion annual sales, 2008 annual report
http://media.pfizer.com/files/annualreport/2008/annual/review2008.pdf

24

http://
www.cbo.gov/doc.cfm?index=7615

L
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16



Indirect costs
:

o

P
re
-
clinical:
$
214

million

o

C
linical:
$
185

million



Cost of developing a drug per year = $
802 million / 12 years =
$
66
million / drug / year



Median R&D spending out of t
op 20 Pharmaceutical Companies
: $2.25
5 billion



N
umber of drugs in pipeline
for median pharmaceutical company per year:

= R&D spending / cost drug development per year

= $
2.25

billion (Pfizer annual report) /
$
66 million

= 34

drugs
in pipeline



Assume drugs in pipeline are spread evenly across 4 phases of development per year:

= 34 drugs in pipline / 4

= 8 drugs in pipeline



Assume scale
-
up of drugs required primarily for Phase
I clinical.


Total Savings

= Number of drugs in need of scale up for Phase I per year * total savings per drug

= 8/year * $12.4 million

= $99.2 million / year

Pricing Justification



Cost of developing a new drug: $802 million
25



Drug takes on average 12
years to develop
26


Cost of 8 licenses
/year
: $0.4 million

Cost of drug/year
:

$
802

million / 12 years
=
$66.8 million

Percentage of drug development cost: $0.4 million / $66.8 million = 0.6%

Marketing Strategy

& Plan

Lilien Cheminformatics will use a variety of means to reach our customers. A number of these strategies
will be integrated with the development phase of SynPlan. Taking the technology adoption curve into
account, we first need to target the early adopters.

These early adopters will be university research
groups and small pharmaceutical companies. During development we plan to work with these
customers to develop and refine our product as well as promote our product. They will have access to a
beta release

of our software. Often, when one research lab has a useful beta release of software,
researchers within that lab will spread the word to researchers (in other labs). As a result, we know that
if other labs start contacting us to obtain a beta version of S
ynPlan, this marketing strategy is surely



25

http://csdd.tufts.edu/About/History.asp

26

www.cbo.gov/doc.cfm?index=7615

L
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17

successful. We can also use the feedback from users during this period to gauge our success and improve
our product. This marketing strategy carries little financial cost.

Once our software is stable enough to be r
eleased to large pharmaceutical companies we will first
release SynPlan to a large pharmaceutical company such as Pfizer. They will have a trial version of our
software to integrate into their synthesis process. We will ensure that Pfizer is content with o
ur product
and provide improvements and customizations to suit their needs. Members of our team will be sent to
the facilities (where our software is in use), to train users and to aid and facilitate adoption. Thus, our
relationship with Pfizer will serve
as a “poster child”, they will become our spokesperson who will help
spread the word about SynPlan across the industry. Our relationship with Pfizer will aid in making the
jump across the chasm, from early adopters to the early majority/mainstream market a
nd will eliminate
the skepticism around our product by proving that it really works and is greatly beneficial. The
customers in the mainstream market are pragmatists and conservatives, both of which only make
purchasing decisions once they see someone els
e making that purchase
27
. Once a pragmatist sees that
SynPlan is being successfully used by another big pharma such as Pfizer, they will follow suit and make
the purchase. The conservative customers watch the pragmatists, once we have a substantial number o
f
large pharmas happy with our product they too will start making purchases and adopt SynPlan.

Since SynPlan is developed in partnership with the Computational Biology lab at the University of
Toronto, we have a strong network in which we can promote our

product. SynPlan will be offered to
Universities and their researchers free of charge, which will also aid in spreading the word between
researchers about our product. We will also hold talks within the university (and possibly other
universities). Since

many biotech and pharmaceutical companies have head offices in the Toronto area
we hope that researchers and representatives from these companies will attend these talks. Such talks
will be held during development to speak about the advancements in our te
chnology.

During the development phase we will also publish papers about SynPlan in a number of pharmaceutical
and cheminformatics journals. These papers will also highlight advances in the development of our
technology. Publishing an article can cost as m
uch as $2000 (in a high end journal), and is an inexpensive
means to reach our customers since medicinal chemists are actively reading such journals. Below is a list
of journals in which we plan to publish:



Journal of Chemical Theory and Computation:
http://pubs.acs.org/journal/jctcce




Expert Opinion on Drug Discovery:
http://informahealthcare.com/edc




Current Opinion in Drug Discovery & Development
http://www.biomedcentral.com/curropindrugdiscovdevel/



Drug Discovery Today:
http://www.drugdiscoverytoday.com/

(Magazine which reports
developme
nts in drug discovery and related technologies)



Drug Development Research:
http://www3.interscience.wiley.com/journal/34597




Computational Biology and Chemistry Journal:
http://www.sciencedirect.com/science/journal/14769271




Journal of Chemical Information and Modeling:
http://pubs.acs.org/page/jci
sd8/about.html




27

Moore, Jerrery A. Crossing The Chasm. Harper Paperbacks: c. 2002.

L
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18



Journal of Computational Chemistry:
http://www3.interscience.wiley.com/journal/33822/home



Journal of Medicinal Chemistry:
http://pubs.acs.org/page/jmcmar/about.html




Journal of Cheminformatics:
http://www.jcheminf.com


From publishing in aforementioned journals, we hope that pharmaceutical companies will contact us
and become
customers. Our success will not only be based on the number of customers we gain from
our publications, but also the number of citations that we receive from other papers. When other
researchers cite our technology and findings they are also aiding in spre
ading the word about SynPlan.

Lastly, one of the more expensive means of reaching our customers is to attend conferences and trade
shows. We plan to attend conferences during the development phase of our product. These conferences
include those held by eC
hemInfo (
http://www.echeminfo.com
), and various computational chemistry
conferences such as the Canadian Computational Chemistry Conference
(
http://www2.bri.nrc.ca/cccc7
/
). At these conferences we will present the findings published in journals
and network with other members of the chemical and pharmaceutical industry.

When we have finally released the final version of SynPlan, our goal is to attend large industry
trades
hows such as INTERPHEX which is held in New York annually. INTERPHEX showcases the latest
technological innovations across the pharmaceutical industry and attracts around 12,000 people from
pharmaceutical and biotech companies globally
28
. Representatives f
rom top pharmaceutical companies
such as Bristol Meyers Squibb, GlaxoSmithKilne and Novartis regularly attend the conferences and thus
gives us a chance to connect with these companies if we have not already done so. Attending
INTERPHEX costs around $6000
-
$10000 depending on the size of the booth, which will be covered with
the sale of a single license. We plan to have a booth with a few stations available so users can interact
and use SynPlan themselves. We will also hold numerous demos during the show de
monstrating the
benefits and advantages of our software.






28

http://www.interphex.com/RNA/RNA_Interphex/Documents/2009/pdfs/IPX09
-
PostshowRelease
-
v3.pdf


L
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19

Sales Plan





Year 3 Q1: First set of customers: The beta testers during the beta phase are our first target
customers. We expect to reach 200 customers as soon as the product is available. (200
x $40k =
$80m in licenses & 200 x $10k = 2m in support of $10m total)



Year 4 Q1: Through marketing and spread via worth of mouth, new customer is reached.



Year 4 Q3: Through experience in usage, adaptation within companies grows; causing growth is
expected. (2,000 customers = $100m)



Year 5 Q4: Knowledge of our product is widely spread and a large portion of pharmaceuticals
will be seeking us to keep their competitive edge in R&D from small to large companies. (10,000
customers = $500m)



Continued gro
wth is expected beyond 5
th

year till a significant portion of the market is
penetrated.

Development Plan


Year 1

Year 2

Year 3

Year 4

Year 5

Product


Design & Specification






















Alpha Release






















Complete Beta Release






















Training Materials Complete






















Documentation Complete






















Unit Testing Complete






















Integration Testing Complete






















1.0 Release Complete






















1.1 Release Complete






















1.2 Release Complete






















1.3 Release Complete























2.0 Release Complete






















Year3 Q1: First set
of customers

Year 4 Q1: First
non
-
beta sales

Year 4 Q3: Factor
of 10th growth

Year 5 Q4: Factor
of 50th growth

L
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20

Executives

Hire VP Marketing






















H楲攠CEO






















Hire CFO






















Financial


Obtain 1
st

Round Funding






















Obtain 2
nd

Round Funding






















佢O慩a 3
rd

Round Funding






















䕸灥捴敤⁂e敡e
-
敶敮






















Company


Get office























Detailed Milestone Descriptions


Description

Completed Scenario

Cost/Resources

Design & Specification

Engineers architect and
design software
specifications.

Development on code
begins.

Engineering resources.

Alpha Release

Initial feedback
with
academic partners on
prototype.

Detailed feedback from
academic partners on
prototype of tool.

Engineering resources
supporting academic
partners use of tool.

Complete Beta Release

An early release with
major features
included.

Ship beta to early
customer partners’ site
for evaluation.

Engineering resources.

Training/Documentation
Materials Complete

In depth manual and
training material that
allows users to learn
about the tool.

Material ready to be
given to support
engineers to present
and docume
ntation to
ship with product.

Engineering resources.

Unit Testing Complete

In depth test suite for
each module of the tool
with realistic cases from
academic and customer
testing.

Continuous regression
and unit testing system
in place that passes all
tests.

Engineering resources.

Integration Testing
Complete

High level testing of
system including
external components
(reaction database,
user interface)

After testing a
comprehensive list of
customer scenarios, no
show
-
stopper bugs
found.


Engineering
resources.

L
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21

1.0 Release Complete

Full functional and
tested release.

Release product to
customer site.

Engineering resources,
marketing/sales
resources.

1.x Release Complete

Full functional and
tested release with
customer bug fixes and
selected feature
requests.

Release product to
customer site.

Engineering resources,
marketing/sales
resources.

2.0 Release Complete

Full functional and
tested release with
significantly improved
capacity.

Release product to
customer site.

Engineering resources,
marketing/sales
resources.

Obtain 1
st

Round
Funding

Necessary funding for
first year operations
from angels, family,
IRAP and SRED.

Close $1,200,000 in
funding, including
founders investment.

Time for meetings and
presentations.

Obtain 2
nd

Round
Funding

Necessary funding for
first half of year 2

Close $9,000,000 in
funding.

Time for meetings and
presentations.

Obtain 3
rd

Round
Funding

Necessary funding for
ramp up to 1.0 release
and support.

Close $7,00,000 in
funding.

Time for meetings and
presentations.

Detailed Release Descriptions and Goals

Alpha Release:
This
will be an initial prototype to send to academic partners to ensure the core
functionality of the product is implemented. This is intended to aid in developing the core features (
i.e.
retrosynthesis planning engine) but not intended for minor features that are in early stages of
development (e.g. GUI). Having validated with real users, this will aid in our credibility in academia, the
industrial community and potential investors.

Beta Release:
This release contains all the major release features (planning engine). This will be
targeted at friendly industrial companies that will evaluate and simultaneously give feedback on the
product. This release aims to make the product more ro
bust through real customer testing as well as
gain valuable feedback for critical features that can be released in time for 1.0.

1.0 Release:
This is the first feature
-
complete release

that will generate revenue
. It will contain
all
major features and feedback
included from the beta release
. This release will target early adopters who
will want to evaluate our relatively new technology. This release will provide all the major features to
increase the organic chemists’ productivi
ty, however, it is expected that there will be significant areas in
which real
-
world show where the product can be improved.

L
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22

1.x Release:
Minor releases will fix any bugs found by customers as well as in
-
house testing. In addition,
additional features wil
l be implemented based on user feedback of the tool. These releases will be
available to all licenses.

2.0 Release:

This release will include a significantly more powerful planning engine. It will be based
upon previous 1.x releases. Any additional bug
fixes will be implemented as well as major feature
requests that were not able to be put into 1.x releases.

Staffing Plan

* See spreadsheet for details


Year 1

Year 2

Year 3

Year 4

Year 5

Executive Staff

CEO

0

1

1

1

1

CFO

0

1

1

1

1

VP Sales & Marketing

1

1

1

1

1

Software Development Team


Team Lead

1

1

1

1

1

Software Architect

1

1

1

1

1

Developers

2

2

3

3

3

Testers

1

2

3

2

2

DB Specialists

1

1

1

1

1

Other


Customer Support

1

6

26

66

126

Marketing Staff

2

2

2

2

2

Sales People

1

1

2

3

3

Administrative

1

1

1

1

1

Total Employees

13

20

43

83

143


Operations Model

Key Activities

Development and testing of SynPlan is our key activity in order to keep our product up to date.
Members of our staff will be responsible for reading journals,
attending expos and conferences to keep
up with the current pharmaceutical industry findings and trends. They will also be responsible for
publishing papers and presenting at such conferences to educate the community about SynPlan. We will
also dedicate me
mbers of our staff to work alongside customers to educate and train chemists to ensure
they are using SynPlan optimally.


L
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23

Key Resources

Our most valuable resource is our experts in chemistry and computer science. Our experts will have
expertise in both fie
lds which will allow us to bridge the gap between the two disciplines and deliver an
effective chemical planner.


Key Partners

Our main partner is the Uof
T Computational Biology Group. W
e will work alongside them to develop and
test SynPlan. Once we have
developed the beta version of SynPlan we will begin to partner with other
academic departments. These departments will be responsible for beta testing. Chemical reaction
databases provide us with all the known chemical reactions needed for SynPlan to gener
ate plans.
Therefore we will form a key partnership with these database providers so we can have access to the
most reliable and up to date information. Lastly, we will form a partnership with publishing companies
to allow for easy publication of papers t
o expose ourselves and spread the word across the pharma
industry of all the latest research and developments pertaining to SynPlan.



To date, Lilien Cheminformatics has conducted extensive market research and has begun planning for
the development of Syn
Plan. We currently have dedicated experts in chemistry and computer science,
who have already completed research related to the issues of retro synthetic planning. The next steps in
bringing SynPlan to market are as follows:




Complete requirements and desi
gn specification



Begin development cycle: Alpha development will be completed in Y1 Q4, followed by extensive
alpha testing



Acquire larger office space, purchase equipment (computers, databases, servers) to support
development and customers.



Hire marketing

staff in order to gain exposure and engage potential customers



Release beta version to academic departments. These academic departments will be involved in
beta testing (Y2 Q2)



Hire customer support and application engineers.



Go live with 1.0 release



Cus
tomer training and education


To implement the above steps we need the following key operations:


Development/Testing:


We will have a strong development team in order to implement all features and requirements of
SynPlan. The team lead will be responsible for communicating with the in house developers and testers
to ensure the product specifications are being met and that
the product is of high quality. He/she will
also be responsible for communicating with the academic
partners
conducting beta testing, overseeing
their progress and getting appropriate feedback and status updates.


Sales/Marketing:

SynPlan will be sold dir
ectly to customers. We will reach these customers through ads in pharmaceutical
journals, industry papers, trade shows, conferences and word of mouth. Sales and Marketing will
communicate with Development to produce industry papers and schedule such talks
and conferences.
Once a purchase has been made, SynPlan will be distributed to customers on site by an expert
application engineer. This application engineer will be responsible for installing and configuring SynPlan,
L
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24

and will train chemists in the use of
our software.


Customer Support:

Throughout the customer relationship, Lilien Cheminformatics will offer product support by phone,
online troubleshooting documents and most importantly, in person by our expert application engineers.
Our application enginee
rs will be available at the customer’s request for onsite training and help to
ensure customer satisfaction and that SynPlan is being used to maximize productivity and drug
development. The customer support team, made of application engineers, will be resp
onsible for these
duties and maintaining customer relationships.


Management/Administration:

Our management team will be responsible for the hiring of staff, acquiring new office space and for
facilitating any purchases that need to be

made (eg: computers
, servers).


Operations Plan

Outline


Year 1

Year 2

Year 3

Year 4

Year 5

Key Resources


Hire experts in chemistry &
technology






















Key Activities





















Star
t software d
evelopment






















却慲琠
R敳敡e捨

/

R敡摩ng潵牮慬猠






















Atte
nd expos, trade shows
conferences






















Education &

Training Customers






















Key Partner
ships

/

Relationships



Partner with U of T Computational
Biology Lab






















Partner with other Academia






















Partner with Reaction Databases






















Partner with Publishing Companies






















Infrastructure

/

Facilities


Get office






















Purc
hase Computers

/

Databases

/

Servers (for developers)






















Purc
hase and implement Servers

/

Databases (for Customer Support)






















Impl
ement Customer Service
support






















L慵n
捨⁗敢獩e攠⡦o爠
m慲ae瑩tg‫
獵spo牴
)






















L
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25

Financial Model

* See spreadsheet for details

5 Year Pro Forma Income Statement

All Figures are in thousands

Year 1

Year 2

Year 3

Year 4

Year 5

Revenues












Licenses


$
-



$
-



$ 14,160


$ 77,520


$ 414,640


Support Handling


$
-



$
-



$
-



$
-



$
-




Setup Charge


$
-



$
-



$ 177


$ 792


$ 4,214


Training & Support


$
-



$
-



$ 3,540


$ 19,380


$ 103,660


Total Support


$
-



$
-



$ 3,717


$ 20,172


$ 107,874


Total Revenue


$
-



$
-



$ 17,877


$ 97,692


$ 522,514

Expenses












General and Admin













Salaries


$ 60


$ 70


$ 180


$ 180


$ 180



Rent and utilities


$ 48


$ 50


$ 72


$ 72


$ 72



Office Equipment


$ 24


$ 29


$ 41


$ 41


$ 41



Legal Fees


$ 24


$ 24


$ 120


$ 120


$ 120



Accounting Fees


$ 40


$ 40


$ 40


$ 40


$ 40



Insurance


$ 120


$ 120


$ 120


$ 120


$ 120



Other


$ 15


$ 14


$ 20


$ 20


$ 20


Total General & Admin


$ 331


$ 347


$ 593


$ 592


$ 592


Product Development













Salaries


$ 360


$ 420


$ 540


$ 480


$ 480



Datacenter


$ 10


$ 10


$ 29


$ 114


$ 646



Other Equipment


$ 29


$ 34


$ 43


$ 38


$ 38


Total Product Dev.


$ 398


$ 463


$ 612


$ 632


$ 1,165


Sales and Marketing













Salaries


$ 185


$ 240


$ 300


$ 360


$ 360



Advertising & PR


$
-



$ 240


$ 480


$ 480


$ 480



Publications


$ 10


$ 10


$ 20


$ 31


$ 31



Conferences


$ 20


$ 20


$ 20


$ 50


$ 50



Trade Shows


$
-



$ 40


$ 60


$ 80


$ 80



Website


$ 15


$ 5


$ 5


$ 5


$ 5


Total Sales & Marketing


$ 230


$ 555


$ 885


$ 1,005


$ 1,005


Support Handling













Salaries


$ 80


$ 240


$ 840


$ 2,240


$ 4,440



Rent and utilities


$ 24


$ 24


$ 96


$ 264


$ 528



Office Equipment


$ 5


$ 14


$ 50


$ 134


$ 266


Total Support


$ 109


$ 278


$ 986


$ 2,638


$ 5,234


Total Operating Costs


$ 1,068


$ 1,644


$ 3,077


$ 4,868


$ 7,997

Net Earnings Before Taxes


$ (1,068)


$ (1,644)


$ 14,800


$ 92,824


$ 514,517


Taxes (Assume 20%)


$
-



$
-



$ 3,101


$ 18,565


$ 102,903

Net Earnings


$ (1,068)


$ (1,644)


$ 11,699


$ 74,259


$ 411,614




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26

5 Year

Pro Forma Cash Flow


All Figures are in thousands

Year 1

Year 2

Year 3

Year 4

Year 5

Operating Activities











Net Earnings (Before Taxes)


$ (1,068)

$ (1,644)


$ 14,800

$ 92,824


$ 514,517

Depreciation

$
-


$
-


$
-


$
-



$
-


Working Capital Changes

$
-


$
-


$
-


$
-



$
-



Accounts Receivables

$
-


$
-


$
-


$
-



$
-



Other Current Assets

$
-


$
-


$
-


$
-



$
-



Accts Pay And Accrd Expenses

$
-


$
-


$
-


$
-



$
-



Other Current Liab

$
-


$
-


$
-


$
-



$
-


Net Cash Provided/(Used)

$ (1,068)

$ (1,644)

$ 14,800

$ 92,824

$ 514,517

by Operating Activities






Investing Activities












Property And
Equipment

$ (52)

$

(28)

$ (92)

$ (160)

$ (240)

Net Cash Used in Investing
Activities

$ (52)

$

(28)

$ (92)

$ (160)

$ (240)

Financing Activities












Short
-
Term Debt

$
-


$
-


$
-


$
-



$
-



Curr. Portion Ltd

$
-


$
-


$
-


$
-



$
-



Long
-
Term Debt

$
-


$
-


$
-


$
-



$
-



Common
-
Stock

$
-


$
-


$
-


$
-



$
-



Preferred
-
Stock


$ 1,200

$ 1,600

$
-


$
-



$
-



Dividends Declared

$
-


$
-


$
-


$
-



$
-


Net Cash Provided/(Used) by
Financing


$ 1,200

$ 1,600

$
-


$
-



$
-


Increase/(Decrease) In Cash

$ 80

$
(72)

$ 14,708

$ 92,664

$ 514,277

Cash at Beginning

$
-


$ 80

$ 8

$ 14,716

$ 107,380

Cash at End

$ 80

$ 8

$ 14,716

$ 107,380

$ 621,657




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27

Financing Plan

Round 1



Jan Year 1 (
Seed Funding
)

Sources
: Angels, friends, family, founders, IRAP, credit cards.

Total:

$1,200,000


Required activities
:

Development of alpha and beta releases.

Journal paper publishing for core algorithms

Presenting demos

of the algorithms and initial prototypes at conferences.

Evaluation of alpha (prototype) release with academic partners.

Round 2
-

Jan Year 2 (VC Part I)

Sources
: VC.

Total:
$900,000


Required activities
:



Finishing up beta release 1.



Evaluation with
friendly early adopter customers.



Journal paper publishing for beta release.



Presenting demos of the beta 1 at conferences.

Round 3
-

Jun Year 2 (VC Part II)

Sources
: VC, investment conditional on previous milestones.

Total:

$700,000



Required activities
:



Attending trade shows with working product demos.



1.0 Release.



Customer purchase.

Exit Scenario 1


Dec Year 5 (Acquisition

by private equity
)



Conservative valuation using P
/
E

ratio

of
10
.



Net Income: $411 million



Valuation: $8,220 million

Exit Scenario 2


Dec Year 5 (IPO)



Market valuation using P
/
E

ratio

of
16

[1].
29



Net Income: $411 million



Value: $20,550 million




29

Investment U


Biotech Stocks: The Market’s Best Bargain Right Now

November 12, 2009
.
<
http://www.dailymarkets.com/stocks/2009/11/11/biotech
-
stocks
-
the
-
market’s
-
best
-
bargain
-
right
-
now>

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28

Customer Interviews

We have contacted a number of people to get some insights about our product. Since, SynPlan is aimed
at facilitating retrosy
nthesis, we selected chemists belonging to various pharmaceuticals, research labs
and academia as our interviewees. We believe (and it was confirmed through the interviews we
conducted) that the end
-
user/chemist input is the deciding factor in the purchase

of our product by any
pharmaceutical, university or research lab. Hence the information obtained from the chemists is crucial
for the success of our product. In addition, we spoke with chemists working at different levels of the
drug design procedure such

as medicinal chemists, process chemists, industrial chemists, synthetic
chemists etc, to confirm where our product belongs in the drug design pipeline, and how it can be
improved.

The interviews were not structured. However, we tried, at least, to
ascertain the answers to the
following questions:



How are various phases of drug design (design, scale up, synthesis etc) procedure completed at
the moment?



What are some of the difficulties that can be addressed in these phases?



How, and to what extent, c
an a product like SynPlan help? Are they currently using any of our
competitor's products?



What are some of the major flaws they can envision in our product/idea?


A summary of each interview is provided, followed by a summary of insights we gained from th
ese
interviews and how it affected our business plan/model/product.

David Dubins

Faculty at Leslie Dan Faculty of Pharmacy, University of Toronto. Bio Services Pharmaceutical Inc.

David's response confirmed our initial research that synthesis in the lab i
s a painstaking process. It takes
very long. David also mentioned that the team of chemists is limited by the number of starting chemicals
they are aware of. As the commercially available starting compound libraries grow exponentially large,
manual work fo
r the chemist becomes cumbersome and inefficient.

David was very excited by the possibility of a planner that can automate the entire process and suggest
chemical routes for synthesis. David mentioned that almost everything available commercially these
da
ys, such as our indirect competitors, is at best, rudimentary.

He mentioned the need of allowing the chemist to be flexible by suggesting multiple routes vs. a single
one. the final decision should rest on the chemist.

David also pointed us towards an
added value proposition of our product that we were previously
unaware of. While the drugs are still patent protected, competitor companies would try to manufacture
large quantities of that drug to create another, highly similar, yet patentable drug. For i
nstance, if drug A
has been patented by PharmA, PharmB will try to produce drug A in house, and generate different
L
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29

analogs of it (eg. by adding a benign methyl group.) to produce another moleulce B. The new molecule B
can have very similar properties as A,

yet is now patentable by pharmB. Our product can help pharmB
produce drug B using an alternative synthetic route than drug A so it can be patended. Our product can
also offer pharma companies the flexibility of pursuing multiple drug leads and analogs sim
ultaneously
to avoid this patent run off.

A final insight that David provided was that most chemists or biochemists prefer using a program with a
web interface, so that they do not have to install it. Hence, if our product can run calculations on a
remot
e server and just provide a web based front end to the chemists, it would be much preferable than
a stand alone, installable software. This is an important insight in terms of design, however, supporting a
web based service only requires immense compute po
wer on Lilien ChemInformatics' side and restricts
chemists from using in
-
house, proprietary raw material catalogs. We are in the process of conducting
more interviews to find out what percentage of our intended customers are averse to an installable
produc
t.

He was also very keen to be able to try a beta version of the software.

Grace Ng (Medicinal Chemist)


Campbell Family Institute for Breast Cancer Research, Toronto

As a medicinal chemist, the synthesis process takes from a few weeks to a few months. As
a medicinal
chemist you are just trying to produce enough end product to conduct trial experiments, so yield is less
important. It is also worth noting that a medicinal chemist does not start from commercially available
starting materials in general, hence

the chemical plans are not as long (about 4
-
5 steps according to
Grace.) However, Grace mentioned that her own knowledge of chemistry is a limiting factor, hence she
has to constantly search for newer reactions and synthetic plans published by other chemi
sts to make
sure she has explored all possibilities. Currently, Grace and her team mates use SciFinder or Reaxys to
search for existing, previously published synthetic plans. However, it is not very often that they can use
already existing, previously publ
ished syntheses. Hence, a considerable effort still goes into planning a
full fledged product even at the medicinal chemist level. Grace also mentioned that, she and her fellow
medicinal chemists are generally working with multiple 'possible' candidate dr
ug like molecules. Hence,
although the syntheses are shorter, and potentially somewhat easier than they are during a scale up, the
process becomes complicated and longer due to optimization for multiple drug targets.

According to Grace, a planner that help
s plan for the entire synthesis would come in very handy. It
would solve a significant problem. Grace mentioned that have precedented reactions was extremely
important. If the suggested synthesis includes complicated reactions, they

must be accompanied wit
h a
citation for the published paper they come from. Grace also mentioned that toxicology was an
important concern for a medicinal chemist and allowing elimination of the toxic compounds from the
synthesis would be a significant help.

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30

One of the aspects of

SynPlan that Grace was concerned about, was the layout. She wanted it to be
simple, easy to use and intuitive. In addition, she wanted us to make sure that the chemist should be
able to draw in a molecule to search for.

We had also asked Grace about the d
ecision making process for purchases at her work place. She
mentioned that the major decision factor was the user demand. If a few of the end users (chemists in
our case) considered our product useful and wanted to try it out, the purchase would be made. S
o, the
buying power lies, in essence, with the end users or chemists.

Like the rest of our interviewees, Grace was excited about the product and wanted to be signed up for
beta testing as soon as we have a beta version.

Andrew Cooper

Analytical/Process
Chemist
-

Allied Chemicals

Andrew is an analytical chemist and has been a first line lab manager at Allied Chemicals formerly.
During his work at Allied Chemicals, he has worked closely with many process chemists as well.

Andrew also confirmed our hypothe
sis that the process of retrosynthesis was extremely time consuming
and inefficient. Furthermore, he asserted that each chemist was limited by his own knowledge during
the quest for a synthetic plan.

After we explained RetPlan, Andrew was very excited abo
ut the idea of automating retrosynthetic
planning. He mentioned that it should be natural for a computer to do the search, since the starting
materials and the end goal was available.

When asked if he could see chemists using this, his answer was an immed
iate yes. He mentioned that
process chemists generally deal with longer synthetic plans which are time consuming to generate today.
Furthermore, the yield is of extreme importance since the desired drug is needed in industrial quantities.

Andrew mentioned

that stereochemistry and chirality should be extremely important factor of the
target software, and this is one area where most of our competitors are lacking. He also elucidated the
need to report all the necessary conditions such as pressure, temperatur
e and time taken for a reaction.

Andrew was also excited to keep in touch with us and help with the beta testing of the product as well
as for any additional design/product insights/brainstorming we might need.

Notes

Some of the salient points of the cust
omer interviews and how they are reflected in our future activities
are listed below:

1.

All the interviewees confirmed our hypothesis that we are trying to solve a real world problem,
which has a willing customer base.

2.

We confirmed that our product will redu
ce time and increase productivity of the chemists and
consequently the profit margin of the pharmaceuticals.

L
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31

3.

We also confirmed that our competitors seriously lack in certain areas which are deemed crucial
by the chemists such as precedented chemical rules,

stereochemistry etc.

4.

At least one customer mentioned the need to make our product a web service. However, the
use of SynPlan as a web service can be limiting for the customers since many pharmaceuticals
have their in house raw material catalogs which are
not available for remote/third party use. We
are going to conduct further interviews to ascertain the importance to our customers of SynPlan
being a web service instead of an application.

5.

Toxicology turned out to be an important factor for the medicinal ch
emists. We see another
potential product which can predict toxicology of a particular reaction. The suggested product
can use existing databases and chemical journals combined with learning algorithms to predict
toxicology.

6.

While our initial targets were t
he medicinal chemists, we notice that the process chemists have
to deal with longer, more complicated synthetic plans. Furthermore, the time and yield are of
importance. Whereas, the medicinal chemists tend to start from intermediate products, and are
less

concerned about optimal yield. Hence, we have shifted our focus to make process chemists
our main targets, followed by the medicinal and synthetic chemists.

Expert Interviews

Malcolm Bersohn

Prof. Emeritus Chemistry, University of Toronto

Malcolm has work
ed on retrosynthetic planning for about 2 decades now. He designed one of the first
retrosynthetic planners a few decades back.

Malcolm feels that there was, and there is a need for automating retrosynthesis. Furthermore, his
interactions with chemists an
d pharmaceuticals during his research and sales of his product, confirm
that the community is open to such a tool. However, Malcolm cautioned about the marketing strategy.
According to him, the retro
-
synthetic planner should never be marketed or advertised

as a replacement
for human judgement. Since the target markets is the chemists, the planner should not, and cannot be
the chemist replacement. Malcolm also noted the need for stereo
-
chemistry in a planner, since it was
and remains, an important but lackin
g feature.

Abraham Heifets

PhD Candidate, AI/Computational Biology Lab, University of Toronto. (Former Researcher at IBM J.
Watson Research Center).

Abraham is a theoretician and an expert in computational search. According to Abraham, the biggest
challeng
e of previous efforts such as Malcolm's has been a lack of what he terms as 'efficient computer
science'. Almost all previous efforts in retrosynthetic planning have failed to find a balance of efficient
computer science and accurate chemistry. Planners co
ming out of chemistry labs such as Malcolm's,
made use of accurate chemistry while being computationally inefficient. This has prevented a
widespread use of previous planners in the industry.

L
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32

However, Abraham believes that, in the past few years, there ha
ve been significant improvements and
research conducted in the fields of heuristic search and computational planning. Yet, none of the
existing retrosynthetic planners makes use of these technological advances. Hence, according to
Abraham, right now is a r
ipe time to design a retrosynthetic planner, which, not only has accurate
chemical capabilities, but also makes searching for plans feasible due to state
-
of
-
the
-
art search and
planning capabilities.

IP Strategy

Lilien Cheminformatics plans to use Trade
Secrets, Copyrights and Trademarks as our IP strategy to
protect the magic behind our innovative chemical planner.

Trade Secrets

We have chosen to keep our source and its ideas a trade secret. Patents will require us to make the
details of our system and a
lgorithm public, even in its early stages. We believe the publication of our
algorithm will invite competition. For instance, once one company reads the details of patent they may
feel inspired to create a better algorithm. Software patents are also not co
mpletely effective since
software cannot be patented under Europe Patent Office.

As with other competitors in our market, our IP strategy consists mainly of trade secrets. The details of
our algorithm will remain a secret through the signing of Non
-
Disclos
ure Agreements by our employees
and collaborators. If an investor wants to know the low
-
level details of our system, then they too will be
required to sign an NDA. From day one each employee we hire will sign an NDA, which is included on the
following page
s.

The NDA attached is just a guideline, but will cover all aspects of confidentiality, ownership, non
-
competition, etc. Employees are only permitted to talk about our trade secrets amongst other
employees, and must not disclose any information regarding
our system and algorithm, business
strategy, and private financial records to any third party. All work completed by the employee will
become the property of Lilien Cheminformatics. It also addresses the issues of non
-
competition;
employees must not work f
or our competitors during their employment with Lilien Cheminformatics and
10 years after, should their employment be terminated. They may not divert any potential
customers/business away from our company. They also agree to not solicit or hire away existi
ng staff
members to a competitor, or solicit existing employees to start their own business (in competition with
Lilien Cheminformatics). If an employee, collaborator, partner or investor breaks any of the terms
outlined in the NDA, we reserve the right to

take legal action.

The database containing the source code of our software will be password protected, and access will
only be given to our developers. Should any of our source code be leaked, we reserve the right to take
action against the employees res
ponsible.

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33

Copyrights

We will register our source code as a copyright with CIPO. This will help protect us from pirated software.
The cost is $65 for the certificate which will facilitate matters (and prove our copyright), should we need
to take action ag
a
inst copyright infringement.

Trademarks

The product name SynPlan and our logo will be registered as a trademark, so it becomes a recognizable
brand across the pharmaceutical industry. SynPlan is not currently registered as a trademark by any
other compan
y, and therefore we plan to pursue registration.

The cost of registration is fairly low, and is one of the most economical solutions to product our brand.
Application and registration will cost $450. We will also incur additional costs, $700
-
1000 through h
iring
a trademark agent to assist with registration. This agent will help ensure our application is complete,
conduct addictional research in the field to ensure our trademark is valid, and lastly if required, handle
the situation where another party oppos
es our trademark application.

Lilien Cheminformatics’ legal services provider will aid in administering Non
-
Disclosure Agreements, and
deal with any agreement violations should they occur. They will also aid in prosecuting copyright
infringement, should th
e situation arise. In our financial model, we allocate $24,000/year from years 1
to 2, and $120,000/year from year 3 onwards, in spending to our legal services provider.



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34

NON
-
DISCLOSURE AGREEMENT


THIS NON
-
DISCLOSURE AGREEMENT (the "Agreement") dated thi
s _______ day of

______________,_______

BETWEEN:


Lilien Cheminformatics

(the "Employer")

OF THE FIRST PART

-

AND
-

___________________________

(the "Employee")

OF THE SECOND PART

BACKGROUND:


1.

The Employee is currently or may be employed as an
employee with the Employer for the position of:
_______________(Software Developer/Tester/Etc). In addition to this responsibility or position (the
"Employment"), this Agreement also covers any position or responsibility now or later held with the
Employer
.

2.

The Employee will receive from the Employer, or develop on the behalf of the Employer, Confidential
Information as a result of the Employment (the 'Permitted Purpose').

IN CONSIDERATION OF

and as a condition of the Employer employing the Employee and the

Employer providing
the Confidential Information to the Employee in addition to other valuable consideration, the receipt and
sufficiency of which consideration is hereby acknowledged, the parties to this Agreement agree as follows:

Confidential Informati
on

1.

The Employee acknowledges in any position the Employee may hold, in and as a result of the Employee's
employment by the Employer, the Employee will, or may, be making use of, acquiring or adding to
information about certain matters and things which are
confidential to the Employer and which
information is the exclusive property of the Employer, including, without limitation:


a.

'Confidential Information' means all data and information relating to the business and
management of the Employer, including propr
ietary and trade secret technology and accounting
records to which access is obtained by the Employee, including Work Product, Production
Processes, Other Proprietary Data, Business Operations, Computer Software, Computer
Technology, Marketing and Developm
ent Operations, and Customers. Confidential Information
will also include any information that has been disclosed by a third party to the Employer and
governed by a non
-
disclosure agreement entered into between the third party and the Employer.
Confidentia
l Information will not include information that:


i.

is generally known in the industry of the Employer;

ii.

is now or subsequently becomes generally available to the public through no wrongful
act of the Employee;

iii.

the Employee rightfully had in his possession pr
ior to the disclosure to the Employee by
the Employer;

L
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35

iv.

is independently created by the Employee without direct or indirect use of the
Confidential Information; or;

v.

the Employee rightfully obtains from a third party who has the right to transfer or
disclose

it.

b.

'Work Product' means work product resulting from or related to work or projects performed or
to be performed for the Employer or for clients of the Employer, of any type or form in any stage
of actual or anticipated research and development;

c.

'Producti
on Processes' means processes used in the creation, production and manufacturing of
the Work Product, including but not limited to formulas, patterns, molds, models, methods,
techniques, specifications, processes, procedures, equipment, devices, programs,
and designs;

d.

'Other Proprietary Data' means information relating to the Employer's proprietary rights prior to
any public disclosure of such information, including but not limited to the nature of the
proprietary rights, production data, technical and
engineering data, technical concepts, test data
and test results, simulation results, the status and details of research and development of
products and services, and information regarding acquiring, protecting, enforcing and licensing
proprietary rights (
including patents, copyrights and trade secrets);

e.

'Business Operations' means internal personnel and financial information, vendor names and
other vendor information (including vendor characteristics, services and agreements), purchasing
and internal cost
information, internal services and operational manuals, and the manner and
methods of conducting the Employer's business;

f.

'Computer Software' means all sets of statements, instructions or programs, whether in human
readable or machine readable form, that a
re expressed, fixed, embodied or stored in any manner
and that can be used directly or indirectly in a computer ('Computer Programs'); any report
format, design or drawing created or produced by such Computer Programs; and all
documentation, design specifi
cations and charts, and operating procedures which support the
Computer Programs;

g.

'Computer Technology' means all scientific and technical information or material pertaining to
any machine, appliance or process, including specifications, proposals, models,

designs, formulas,
test results and reports, analyses, simulation results, tables of operating conditions, materials,
components, industrial skills, operating and testing procedures, shop practices, know
-
how and
show
-
how;

h.

'Marketing and Development Operat
ions' means marketing and development plans, price and
cost data, price and fee amounts, pricing and billing policies, quoting procedures, marketing
techniques and methods of obtaining business, forecasts and forecast assumptions and volumes,
and future pl
ans and potential strategies of the Employer which have been or are being
discussed; and

i.

'Customers' means names of customers and their representatives, contracts and their contents
and parties, customer services, data provided by customers and the type, q
uantity and
specifications of products and services purchased, leased, licensed or received by clients of the
Employer.

Obligations of Non
-
Disclosure

2.

The Employee must not disclose the Confidential Information.

3.

The Confidential Information will remain the
exclusive property of the Employer and will only be used by
the Employee for the Permitted Purpose. The Employee will not use the Confidential Information for any
purpose that might be directly or indirectly detrimental to the Employer or any of its affili
ates or
subsidiaries.

4.

The obligations to ensure and prevent the disclosure of the Confidential Information imposed on the
Employee in this Agreement and any obligations to provide notice under this Agreement will survive the
expiration or termination, as t
he case may be, of this Agreement and those obligations will last
indefinitely.

L
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36

5.

The Employee may disclose any of the Confidential Information:

a.

to such of his employees, agents, representatives and advisors that have a need to know for the
Permitted Purpose

provided that:


i.

the Employee has informed such personnel of the confidential nature of the
Confidential Information;

ii.

such personnel agree to be legally bound to the same burdens of non
-
disclosure and
non
-
use as the Employee;

iii.

the Employee agrees to take al
l necessary steps to ensure that the terms of this
Agreement are not violated by such personnel; and

iv.

the Employee agrees to be responsible for and indemnify the Employer for any breach
of this Agreement by his personnel.

b.

to a third party where the Employer

has consented in writing to such disclosure; and

c.

to the extent required by law or by the request or requirement of any judicial, legislative,
administrative or other governmental body.

Avoiding Conflict of Opportunities

6.

It is understood and agreed that
any business opportunity relating to or similar to the Employer's current
or anticipated business opportunities coming to the attention of the Employee during the Employee's
employment is an opportunity belonging to the Employer. Accordingly, the Employee
will advise the
Employer of the opportunity and cannot pursue the opportunity, directly or indirectly, without the
written consent of the Employer.

7.

Without the written consent of the Employer, the Employee further agrees not to:

a.

solely or jointly with othe
rs undertake or join any planning for or organization of any business
activity competitive with the current or anticipated business activities of the Employer; and

b.

directly or indirectly, engage or participate in any other business activities which the Em
ployer, in
its reasonable discretion, determines to be in conflict with the best interests of the Employer.

Non
-
Solicitation

8.

Any attempt on the part of the Employee to induce others to leave the Employer's employ, or any effort
by the Employee to interfere

with the Employer's relationship with its other employees and contractors
would be harmful and damaging to the Employer. The Employee agrees that during the term of the
Employment and for a period of five (5) years after the end of term of the Employment,

the Employee will
not in any way, directly or indirectly:

a.

induce or attempt to induce any employee or contractor of the Employer to quit employment or
retainer with the Employer;

b.

otherwise interfere with or disrupt Employer's relationship with its employe
es and contractors;

c.

discuss employment opportunities or provide information about competitive employment to any
of the Employer's employees or contractors; or

d.

solicit, entice, or hire away any employee or contractor of the Employer.

This obligation will be

limited to those that were employees or contractors of the Employer when the
Employee was employed

Non
-
Competition

L
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37

9.

Other than through employment with a bona
-
fide independent party, or with the express written consent
of the Employer, which will not be unreasonably withheld, the Employee will not, during the continuance
of this Agreement or within ten (10) years after t
he termination or expiration, as the case may be, of this
Agreement, be directly or indirectly involved with a business which is in direct competition with the
particular business line of the Employer that the Employee was working during any time in the la
st year of
employment with the Employer.

10.

For a period of ten (10) years from the date of termination or expiration, as the case may be, of the
Employment, the Employee will not divert or attempt to divert from the Employer any business the
Employer had enj
oyed, solicited, or attempted to solicit, from its customers, prior to termination or
expiration, as the case may be, of the Employment.

Ownership and Title

11.

The Employee acknowledges and agrees that all rights, title and interest in any Confidential Inform
ation
will remain the exclusive property of the Employer. Accordingly, the Employee specifically agrees and
acknowledges that the Employee will have no interest in the Confidential Information, including, without
limitation, no interest in know
-
how, copyri
ght, trade
-
marks or trade names, notwithstanding the fact that
the Employee may have created or contributed to the creation of the same.

11.

The Employee does hereby waive any moral rights that the Employee may have with respect to the
Confidential Information
.

12.

The Employee agrees to immediately disclose to the Employer all Confidential Information developed in
whole or in part by the Employee during the term of the Employment and to assign to the Employer any
right, title or interest the Employee may have in t
he Confidential Information. The Employee agrees to
execute any instruments and to do all other things reasonably requested by the Employer (both during
and after the term of the Employment) in order to vest more fully in the Employer all ownership rights
in
those items transferred by the Employee to the Employer.

Remedies

13.

The Employee agrees and acknowledges that the Confidential Information is of a proprietary and
confidential nature and that any disclosure of the Confidential Information to a third party

in breach of
this Agreement cannot be reasonably or adequately compensated for in money damages and would cause
irreparable injury to the Employer. Accordingly, the Employee agrees that the Employer is entitled to, in
addition to all other rights and reme
dies available to it at law or in equity, an injunction restraining the
Employee and any agents of the Employee, from directly or indirectly committing or engaging in any act
restricted by this Agreement in relation to the Confidential Information.

Return
of Confidential Information

14.

The Employee agrees that, upon request of the Employer, or in the event that the Employee ceases to
require use of the Confidential Information, or upon expiration or termination of this Agreement, or the
expiration or terminati
on of the Employment, the Employee will turn over to the Employer all documents,
disks or other computer media, or other material in the possession or control of the Employee that:

a.

may contain or be derived from ideas, concepts, creations, or trade secret
s and other proprietary
and Confidential Information as defined in this Agreement; or

b.

is connected with or derived from the Employee's services to the Employer.

AGREED AND ACCEPTED:

By: _________________________




Witness:____________________

L
ILIEN
C
HEMINFORMATICS




38

Signature:__
__________________




Signature:___________________

Date:________________________