April 18th, 2014

UC Davis Big Bang Business Competition

Business Summary

Benjamin M. Samudio, CEO

A Social Good Endeavor Toward New and Better Medicines

What We DoWe at MedWorks Medicine by Design provide an online collaborativeplatform through which we engage students, the public, and medicalresearchers (innovation partners) in learning about and designing medicinecomputationally. We then process the information which is generated anduse it to sell innovative and actionable knowledge to medicine makers(customers) which decreases their cost of making medicine by an average of20%. Due to these cost savings, our methods lower the barriers involved ingetting medicine to those who need it (beneficiaries).

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Innovation partners(medicine designers)

Customers(medicine makers)

Beneficiaries(medicine beneficiaries)

Online platform for designingmedicine computationally www.WeDesignMedicine.com

Cancerous cells

Control center

Human cell

Protein (target)

Ligand(potential drug)

KeyLock

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Site of protein-ligand interactions

http://www.youtube.com/watch?v=NZwRR8Xmsu8

Within a cell, communication occurs between the control center of the cell andthe rest of the cell, facilitated by large molecules known as proteins. Whenthese proteins fail, miscommunication occurs and may lead to diseases such ascancer. The goal of our customers is to make a small and unique molecule,known as a ligand, which interacts with the protein in a very dynamic andspecific way, like a lock and key, in order to prevent this miscommunication.Understanding these interactions is crucial to finding and improving medicine.

Understanding Disease: Cancer

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The Problem: The Blind Search

2) Build

+

1) Guess ?3)Test

Currently, our customers face a drug development process which is fraught withtrial and error. They assemble ligands from “chemical parts”, much likeassembling Lego® pieces into a unique structure, in their quest to find the oneligand which has just the right structure and properties to specifically interactwith the protein target. There is a huge number of possible ligands (about 1060).The underlying problem is that our customers can’t “see” how any one ligandinteracts with the protein target. This means that they are limited to guessingabout which ligands to assemble and little is learned once they test theseligands, resulting in a “blind” search and the fact that, on average, to make onedrug costs our customers $1.8 billion, has a 95% failure rate, and takes 13.5years. These trends are rapidly increasing making this process unattractive.

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Our Solution: The Power of Computers

1) Build

+ Real

2)Test

Within the last 5 years, computers have become powerful enough toadequately model proteins. It is now possible to build ligands and test themagainst a protein target all within a computer, allowing users to “see” howligands and proteins interact. This capability offers several advantages; 1) theligand search space is vastly narrowed, 2) just about any ligand can be tested,not just the ones that currently exist, enabling innovative exploration, and 3)insight is generated about which interactions work, allowing for quickeroptimization of ligands. Virtual idea-build-test cycles are shorter, quicker, andcost 1/100th the time and finances of their real-world counterparts leading toinnovative and efficient searching even before any real ligands have been built.

Virtual

+

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Our Solution: Innovation by People + Power of Computers

We humans have intuition, a powerful ability to find patterns, passion,creativity, and the spirit of exploration. When these attributes are combinedwith the advantages brought about by computers, a potent solution to findingand improving medicine emerges. At MedWorks Medicine by Design, we host afree, open, and collaborative platform which enables anyone with a browser tobuild, explore, and test ligand designs against disease target models. We thenrefine these designs into potential medicine starting points and sell them to ourcustomers, saving them time, money, and resources in the search for medicine.This lowers the barriers involved in getting medicine to our beneficiaries.

Innovation partners(medicine designers)

Medicine design platform

Customers(medicine makers) Beneficiaries

Refinement

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Our Services

In pursuit of a particular medicine, medicine makers typically synthesize thentest a large numbers of ligands, known as a library, against a particular proteintarget in a process known as High Throughput Screening (HTS). The HTSmethod is essentially an expensive and blind search through ligand possibilities.We assemble a collection of ligands (potential medicine starting points), whichwere developed from our medicine design platform, into a virtual ligand library.We then sell this library to our customers who synthesize the ligands in thelibrary and test them against a disease target. Since we utilize a knowledgebased approach to designing these ligands, they are more focused on thedisease target and enrich the possibilities for producing an effective medicine.

HTS robots Chemical synthesisMedicine

The Market

• Number of academic drug discovery centers has increased from 12 to 100 since 2001.

• Beta Testing & Market Research

• Ex: University of New Mexico, Center for Molecular Discovery; Johns Hopkins University, Ion Channel Center; University of Kansas, Specialized Chemistry Center

100 Academic Research

Institutions

• Combined, over $11.8 billion/yr spent on R&D.

• Ex: Isis Pharmaceuticals, Ipsen Group, United Therapeutics

4,300 Biotech Companies

• Combined, over $122 billion/yr spent on R&D

• Ex: Johnson & Johnson, Pfizer, Novartis.

~50 Large Pharmaceutical

Companies

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How we enter the market

Initially our innovation partners (students, the public and researchers) will learnto design medicine using our proprietary models via our open online platform.We will then refine the information and have the platform available for thegeneral public. Further refinement will generate actionable knowledge whichwe sell to medicine makers in the form of virtual ligand libraries for enhancingreal HTS (vHTS). We will charge $10K for each virtual ligand library (vHTS).

RefinementAcademia

Public DatabaseNRO disease targets

Grants/Donations/Consultation

The publicPublic/Private Databases“Popular” disease target

Advertisements/Donations

ResearchersPrivate Databases

Profitable disease targetFees for Services ($10K)

Refinement

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The Competitive Landscape

Our competitive advantage lies in combining the power of computers to modelhow ligands and their protein targets interact, ability to store large amounts ofdata, and find patters (dynamics based) with the creativity, intuition, andpassion of collaborating human designers (crowd design).

Companyor Method

Ligand based Structurebased

Crowd computing

Dynamics based

Crowd design

Quantum cures

AutoShim

Numerate

Experiments(real)

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Our Technological Advantage

Our technological advantage lies in three main areas:1) Browser based design of medicineThe medicine design portion of our platform,www.WeDesignMedicine.com, is completely browserbased thereby being operating system independentand obviating the need for downloading or keepingup with software revisions.2) Crowd computingOur platform leverages the collective computationalpower of many individual browsers which arededicated to running the calculations that are a partof the design of medicine.3) Our computational models and databasesOur proprietary computational models and databasesare used to test and store ligands which have beendesigned in web browsers. They have a low operatingcost, are easily scalable, and are secured.

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Our Team

Benjamin M. Samudio, CEOEducation: Ph.D. Candidate, Chemistry, UC Davis

B.Sci. Chemistry, Cal State BakersfieldResearch: Quantum mechanical / molecular mechanical simulationsExperience: Associate Instructor, Physical Chemistry, UC Davis

Business Development Fellow, UC DavisBiomedical Research Intern, NovartisMedical Journeyman, United States Air Force

Kevin DeMarco, CTOEducation: Ph.D. Student, Biophysics, UC Davis

M.Sci. Physics, U. Central FloridaB.Sci. Computer Science, U. Central Florida

Research: Protein modeling, molecular dynamics, and drug designExperience: Teaching Assistant, Chemistry, UC Davis

Physical sciences Intern, Lawrence Livermore National Lab

Nithin Dhananjayan, COOEducation: Ph.D. Student, Biophysics, UC Davis

M.Sci. Electrical Engineering, StanfordB.Sci. Computer Engineering, Virginia Tech

Research: Protein simulation and structural analysisExperience: Teaching Assistant, Chemistry, UC Davis

Software engineering and hardware design, Intel Corp

We Provide: A comprehensive combinationof education, research, andindustry experience.

Our Passion: To simultaneously streamline the development of targeted therapeutics while improving science education.

Business Model

Revenue: vHTS ($10K per vHTS)Cost: cost of computing resources

* Free Academia beta test June 2014–June 2015** To market in June 2015

$ in (000's) 2014 2015 2016 2017 2018

Price (per vHTS) 0 10 10 10 10

Operating Cost 98 132 124 110 90

Net Income -98 0 8 22 42

Projects (#vHTS) 0 20 50 100 500

Annual Profit 0.0 1.0 415.0 2175.0 20845.0

Revenue Drivers:# of customers, number of projects per customer

Cost Drivers: # of Users, amount of data, cost of sale, legal hurdles

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Financial Projections

$ in (000's) 2014 2015 2016 2017 2018

Revenue 0 2640 6600 13200 66000

Team 0 1200 1650 2250 3000

Amazon Cluster 78 155 155 155 155

Outsourced Dynamics 90 660 3000 6000 30000

Infrastructure 30 80 110 150 200

Legal/IP 65 200 500 1000 5000

Research & Development 0 264 660 1320 6600

Other Cost 30 80 110 150 200

Operating Cost 293 2639 6185 11025 45155

Operating Cost/Project 98 132 124 110 90

Net Income/Year -293 1 415 2175 20845

Net Income/Project -98 0 8 22 42

Net Income/Year -293 1 415 2175 20845

Net Income (5-Year Model) -293 -292 124 2299 23144

Biotech/Pharma Projects 0 20 50 100 500

Academia Projects 3 2 0 0 0

Headcount 3 8 11 15 20

0% 6% 16% 32%

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Summary and Next Steps

Positive cash flow by end 2015ROI by 2016

32% Margin by 2018

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Exit Strategy: Sell to competitor in 2018Valuation = $50MM

Seeking $1,000,000Beta Testing Academia (2014-2015)Sales & Marketing Full Market Launch (2015)Sales & Marketing Scale Up (2016)