collaborative medicinal chemistry research

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We describe what we have learned from four years of collaborating across the industry/not-for-profit boundary. Over this time we pursued multiple projects and some of the lessons learned are described here. Many large pharma companies have reduced their research activity at the very early, hit- and lead- seeking phase of research. To compensate, organisations are becoming more porous and working more collaboratively in risk-sharing arrangements. Both parties need to give up some control, but gain a great deal in return

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  • 1. Collaborative MedicinalCollaborative Medicinal Chemistry Research: Building More Porous OResearch Organisations The Academic-Industrial Interface in 21st Century Drug Discovery Tuesday 24 June 2014 David Andrews*, Andy Merritt, Martin Swarbrick

2. Outline of Talk Introduction to AstraZenecas Open Innovation Efforts Examples of compound collection collaborations C t d ll b ti i l ti D i M k T t A l Case study : collaborating in real time : DesignMakeTestAnalyze - Opportunities - IssuesIssues - Solutions Open Innovation Platform Future Outlook 2 David M Andrews | 24 June 2014 R & D | Oncology 3. AstraZeneca is driving science through collaborations more than 90 partnerships in the last three years 4. Three examples of how we are helping to drive Open Innovation across our industry: Leveraging compound collections to share to maximise value TB D A l tTB Drug Accelerator Delivering support for neglected disease strategy and sharing libraries to find di i f lif Delivering reciprocal access to high quality chemical start points with libraries th $MM Delivering early access to new target ideas and partnerships with d i LG t new medicines for life- threatening neglected diseases worth $MMs academic LG centres, with first right of refusal on targets at LO P id ll i ( ) Hi F dProvide collection(s) Hits Freedom-to-use Clean; with a clear exit strategy 5. Medicinal chemistry within different collaborative discovery model settingsy g Model Description Advantages Challenges Strategic long-term, shared risks motivation and engagement, true- role definition, manage- Model Description Advantages Challenges Strategic long-term, shared risks motivation and engagement, true- role definition, manage-S a eg c Alliance* o g te , s a ed s s and incentives o a o a d e gage e , ue type collaboration, learning/expertise, cost effective o e de o , a age ment, processes, accountability, IP Industry- risks & rights at clear roles IP and decisions utilizing full potential of S a eg c Alliance* o g te , s a ed s s and incentives o a o a d e gage e , ue type collaboration, learning/expertise, cost effective o e de o , a age ment, processes, accountability, IP Industry- risks & rights at clear roles IP and decisions utilizing full potential ofIndustry- sponsored risks & rights at industry sponsor clear roles, IP and decisions, speed, flexible utilizing full potential of the team, costs Government/ Charity research project grant approval neglected diseases, diverse groups and skills longer term planning bureaucracy, IP, management Industry- sponsored risks & rights at industry sponsor clear roles, IP and decisions, speed, flexible utilizing full potential of the team, costs Government/ Charity research project grant approval neglected diseases, diverse groups and skills longer term planning bureaucracy, IP, managementCharity- funded** approval and skills, longer term planning, cost effective management Crowd- use of the entire Easy to accommodate, low cost, IP, management of Charity- funded** approval and skills, longer term planning, cost effective management Crowd- use of the entire Easy to accommodate, low cost, IP, management of sourcing MedChem community powerful in idea generation design ideas Innovation incubator on-campus model training, tool compounds, line of sight IP, limited to early discovery phases sourcing MedChem community powerful in idea generation design ideas Innovation incubator on-campus model training, tool compounds, line of sight IP, limited to early discovery phases Precompeti- tive consortia common interest in developing tools cost effective, learning/expertise management, IP, limited to early discov. H Wild et al Angew Chem Int Ed 2013 52 2684 Precompeti- tive consortia common interest in developing tools cost effective, learning/expertise management, IP, limited to early discov. H. Wild et al., Angew. Chem. Int. Ed. 2013, 52, 2684. * R. Wellenreuther et al., Drug Discov. Today 2012, 17, 1242. * R. Williams et al., Drug Discov. Today 2012, 15, 1359. * D. Andrews et al., Drug Discov. Today 2014, 19, 496. ** A.L. Hopkins et al. Nature 449, 166 6. Setting Up the Collaborations The Initial Model Shared Series of Initial HTS Hit Shared Series of Interest The Problems What happens to the hits that dont go anywhere? Led to a reluctance to unblind structuresLed to a reluctance to unblind structures Two countries divided by a common language : we used slightly different terminology and acronyms for the same things The Solution Create an agreement that gives the chemists the maximum freedom to work innovatively and i ti llsynergistically Control the risk of inadvertent reach-through into the broader proprietary information or the parent organizations Agree common terminology, common ground rules 6 David M Andrews | 24 June 2014 R & D | Oncology 7. Opportunities in Compound Collaboration Ownership of compound series rests with the originator until initial liabilities are mitigated Prevents the non-originating parties collection becoming populated by compounds that cant progress Incentivizes teams to overcome initial liabilities Productive SAR triggers shared ownership and a fully collaborative research optimization programprogram 7 David M Andrews | 24 June 2014 R & D | Oncology 8. Additional Impacts of Clearer ground Rules Allows testing of newer compounds 16 18 20 12 14 16 Years 6 8 10 Years 2 4 6 0 10 20 30 40 50 60 70 80 90 100 0 C l ti t 8 Cumulative percent David M Andrews | 24 June 2014 R & D | Oncology 9. Additional Impacts of Clearer ground Rules Allows testing of quality compounds 1 2 0 1 3 4 6 Calculated logD distribution-2 -1 4 Rotatable bonds 2 12 8 10 -4 -3 2 5 6 7 12 3 4 4 5 7 8 Rings 2 5 6 and expansion into full deck screening Number of Acceptors 2 3 4 9 10 11 screening 9 2 11 David M Andrews | 24 June 2014 R & D | Oncology 10. Issues to Overcome. .and solutions Design Make Test Analyze What should Who? External database? Preferred we make? Priority? Who? Route? database? Post data between partners? workflows / analysis tools? 10 David M Andrews | 24 June 2014 R & D | Oncology 11. Collaboration Tools Ch T X Capture of design ideas and outcomes (knowledge management) ChemTraX p g ( g g ) Platform for real time collaboration between partners and service providers Easy visibility of on going chemistry within a project and planned next rounds of chemistry, ensuring optimal deployment of resources Built to support todays ways of working with partners and CROs where information visibility and user functionality is easily controlled to fit all modes ofinformation visibility and user functionality is easily controlled to fit all modes of operation f f Information access is set at the project level, enabling easy set up of multiple projects to work with multiple organizations 11 David M Andrews | 24 June 2014 R & D | Oncology 12. Overview of Features ChemTraX Tracking Board Process Steps a design set follows from conception Overview of Features Steps a design set follows from conception through to completion Color Design Set Multi parameter way of visualizing information Here we see color by organization that is assigned the design set for synthesis Design Set A collection of chemical structures Swim Lanes Multi parameter way of separating the design sets This example shows split by priority of design set 12 David M Andrews | 24 June 2014 R & D | Oncology designed to address a specific project issue (potency, solubility etc) This example shows split by priority of design set 13. Design Sets Sharing Ideas and Compounds to SynthesizeSharing Ideas and Compounds to Synthesize Collaborative sharing of: Design hypotheses C d t id f th i Compounds to consider for synthesis Status of individual compounds (in synthesis, complete etc) R & D | Oncology y , p ) Design set outcomes 14. Data Sharing Partner 2Partner 1 Visualisation Visualisation Query & retrieval Query & retrievalExport and transfer Corporate Database Corporate Database transfer p p Input Input 14 Data generation Data generation 15. PIP5K and PI4K Complex Biology A ideal target area for risk-sharing collaboration N O H O O PI4K O O LY294002 O O O O OO Wortmannin Pharmacological manipulation of cellular PI4P LY294002 Wortmannin pIC50 PI4K

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