1. BioPaths-Catalyze Drug Discovery, Development and Clinical Research www.biopathsinf.com

2. The Race for New Drugs Expensive and growing. –Multi-years, multi-person –Cost estimates are as high as $1 Billion, and increasing safety concerns will add cost Embracement of targeted therapies and stratification of patient populations. –Genetics and lifestyle factors will guide suitability of drugs

3. The Race for New Drugs Identifying potential winners. –New scientific territory and intellectual property –Capturing and evaluating internal AND external projects –Diversity and complexity of information required to arrive at well founded decisions Scientific data (images, sequences, models, scientific reports…) Critical organizational information (project, financial management) Internal proprietary, external commercial, open- source data

4. BioPaths - Faster/Better/Cheaper Get better decisions by harnessing corporate knowledge and integrating all necessary data Make project teams more efficient by facilitating communication and right work at right time Institutionalize translational medicine techniques –Bench to bedside and bedside to bench Make it all fit with current organizational and operational structure

5. Phase IVPhase IIIPhase IIbPhase IIaPhase I Pre- Clinical Phase Candidate Profiling Phase Discovery Life Cycle Management Full Development Early Development Research BioPaths Vision – Link Discovery, Development, Clinic Internal Discovery And Development Licensing Opportunities: Government labs Academic labs Biotechs Translational Medicine How do we manage portfolio of opportunities and feed back clinical learnings to help and facilitate the best projects?

6. BioPaths-Powers Translational Medicine Get required information using translational medicine techniques Target responsive populations with focused clinical studies (achieve greater statistical power with smaller, less expensive clinicals) Mine patient data for early indications of adverse effects, unexpected syndromes Analyze patient populations for SNPs in target genes, metabolizing enzymes

7. Will facilitate patient classification, registries, treatment approach analysis Can score patients against standard representations for both selection/inclusion criteria and early side effect detection Integration with biological process/pathway models allows for clinical results to support more efficient discovery/lead selection BioPaths-Powers Translational Medicine

8. BioPaths- Conduit to external opportunities 5000 Biotechs developing potential therapies, also many academics and government labs Need to understand these in terms of the diseases of interest (pathways affected) Need to compare target enzyme genetics to select best opportunities ADME prediction tools to estimate metabolism issues, or similarity to compounds with known ADME

9. BioPaths Synthesizes Data To efficiently work these issues, the data has to be accessible within a single environment Object modeled approaches and applications can consolidate all of these disparate elements Query tools that can understand the contingencies are critical to success

10. P&G using BioPaths and Research Objects More projects moved into IND –BioPaths contributed to 50% more projects moved to IND More Discovery Projects in portfolio –BioPaths contributed to 30% more projects in portfolio with same budget Faster and more informed decisions –Discovery Project teams reported better ability to make “go/no go” decisions –Discovery Project teams reported feeling better about directions their teams were pursuing

11. P&G using BioPaths and Research Objects-New Applications Reduced time to develop applications –Research Objects reduced time to market for initial development by 50%, follow-on maintenance releases - 80% Reduced application development cost –Research Objects reduced overall development cost - 60% –Common infrastructure dramatically simplified new application integration No Project Failures –P&G experience was that other n-tier application development efforts often failed on budget, delivery or functionality objectives

12. Problems range… Knowledge-representation and integration Distributed systems search and access control Data mining and knowledge management Real-time modeling and simulations Algorithm development and computational complexity Virtual communities and e-collaboration