Medicinal Chemistry Excellence: Efficient and Innovative Solutions for Superior Pre-Clinical Candidates

Transcription

1 Building innovative drug discovery alliances Medicinal Chemistry Excellence: Efficient and Innovative Solutions for Superior Pre-Clinical Candidates Craig Johnstone Evotec AG, X-talks Webinar, June 2017

2 Agenda Introductions and Evotec in brief Creativity, knowledge, experience, and interdisciplinary problem-solving High-quality science, scientific execution, process excellence every day Fastest progress on projects, high-quality drug candidates 1

3 Your Evotec speakers today Background and experience Craig Johnstone EVP, Global Head of Chemistry, Site Head, Toulouse, France >20 years experience, 5 years at Evotec AstraZeneca, Prosidion >70 patents & publications Steve Bromidge SVP, Head of Chemistry Abingdon, UK >20 years experience, 6 years at Evotec GSK and legacy Companies >100 patents and publication 2

4 Adding value to our partners research Innovative and flexible solutions from target ID to pre-clinical candidate The people A wide therapeutic area expertise Integrated drug discovery Flexible deal structures Outstanding scientists (~1000) Experienced project management Pain, oncology, metabolics, CNS, immunology, inflammation, infection, cardiovascular State-of-the-art capabilities Best-in-class technology platforms Integrated collaborations and stand-alone services A world-class drug discovery expertise and platform to accelerate and maximise our partners success 3

5 Our global offering in partnerships Evotec s global footprint >1,200 employees, >1,000 scientists in EU & US Princeton, Branford, Watertown and San Francisco, USA ~110 employees Compound ID, selection and acquisition Compound QC, storage and distribution Cell & protein production ADME-Tox, DMPK Abingdon, Manchester/ Alderley Park, UK ~400 employees Medicinal chemistry ADME-Tox, DMPK Structural biology In vitro & in vivo anti-infective platform/screening Toulouse, France ~300 employees Compound management Hit identification In vitro & in vivo oncology Medicinal chemistry ADME & PK Early drug formulation & Solid form screening Cell, protein & antibody production Hamburg (HQ), Göttingen and Munich, Germany ~430 employees Hit identification In vitro & in vivo biology Chemical proteomics & Biomarker discovery and validation Cell & protein production Antibody discovery 4

6 Blending human creativity, knowledge, science and process for better drug discovery Better outcomes when five key features are successfully blended together Human creativity, insight, intuition, inspiration Drug discovery is still a very organic and human endeavor through true teamwork and partnership Extensive knowledge, experience, expertise, know-how Knowledge of analogous problems enables rapid solutions and anticipation and avoidance of problems Blended together, leads to: Faster progress towards Better quality drug candidates with higher probability of success through development At lower costs for partners Multi-disciplinary awareness and close interactions Toughest problems are at the interface between disciplines Highest quality science thinking and tools Relevant, high capacity test systems, computational/predictive tools High performance processes The right, well-designed experiment, the diligently designed compound, executed rapidly, right first time 5

7 Agenda Introductions and Evotec in brief Creativity, knowledge, experience, and interdisciplinary problem-solving High-quality science, scientific execution, process excellence every day Fastest progress on projects, high-quality drug candidates 6

8 Deep and broad experience, knowledge, know-how Chemistry Leadership Team Craig Johnstone Steve Bromidge Heather Tye Mike Bodkin Ashley Jarvis Rob Riley Gilbert Lassalle Marie-Pierre Fialon Eric Cogo EVP, Global Head of Chemistry, Toulouse site Director SVP, Head of Chemistry, Abingdon VP, Medicinal Chemistry Abingdon VP, Research Informatics, Abingdon VP, Medicinal Chemistry, Abingdon EVP, Global Head DMPK VP, Head of Chemistry, Toulouse Head of Research informatics, Toulouse Head of DMPK, Toulouse >20 years >20 years >10 yrs >15 years >15 years >20 years >25 years 15 years 20 years AZ, Prosidion GSK & legacy Companies Evotec talent Lilly, AZ Domainex, NCE AZ, Fisons Synthelabo, Sanofi Sanofi Sanofi Diabetes, Obesity, inflammation, oncology CNS. GPCRs, transporters, ion-channels GPCRs, kinases, metabolic CNS, pain and inflammation. Ion-channels Oncology, inflammation Enzymes, PPIs Respiratory & Inflammation CV-Thrombosis Oncology Enzymes PPI s Oncology, Antiinfectives, Data management Pharmaceutical sciences for CNS, Oncology, Anti-infectives, Medicinal Chemistry, Computational chemistry, chemoinformatics, Physico-Chemistry, ADME/PK team groups working together for everyday excellence 7

9 Strength & Depth Down to the Bench Representative selection, typical Project Leaders John Barker VP Structural Biology Daryl Walter Jon Bentley Fred Brookfield Mike Prime Alexandre Froidbise Chantal Alcouffe Jérome Meneyrol Research Leader Project Leader Project Leader Project Leader Project Leader Project Leader Project Leader >15 years >15 years >15 years >20 years 15 years >10 years >20 years >10 years Pantherix Roche, GSK GSK, Vernalis Merck & Co Tularik Sanofi Synthelabo, Sanofi Member of Diamond Scientific Advisory Board CNS, pain and inflammation. Ion-channels CNS, metabolic, inflammation Kinases, GPCR Prodrugs Oncology, CNS, kinases GPCR s antiinfective Oncology, Thrombosis, PPI s, GPCRs Synthelabo, Sanofi Kinases, phenotypic appr., other enzymes 8

10 Successful discovery requires problem-solving Integrated thinking and drug hunting experience more success Design & Synthesis SAR Kinetics In Vitro Biology Creating success: Problem-solving & Invention Drug-hunting knowledge and experience MPO Control of Disposition MOA Translational Biology Slick logistics, speed High-level intellectual engagement Best judgment and advice DMPK PK:PD PD2M In Vivo Biology 9

11 Evotec scientists make inventive contributions Strong track record of intellectual input and candidate delivery 1% Other therapeutic areas 20% Respiratory and Inflammation diseases 7% Reproductive health 8% Cardiovascular disease 20% Metabolic disease (incl. CNS targets) 12% CNS disease 13% Oncology 19% Infectious disease Evotec scientists are named inventors on >300 client patents across all target classes >500 publications from collaborations and internal research peer-reviewed journals Track record: >100 lead series developed, >50 pre-clinical candidates delivered 10

12 Maximising knowledge in design Augmenting knowledge and creativity with computational techniques Known properties and short-comings Putative solutions Selection pressure Optimal solutions Existing chemistry Med chem creativity & experience In-silico chemistry RVs and/or rules Conformational hypotheses New ideas Design Ideas Virtual Library Generation Assess Interpret Predicted Predicted Q 2 = 0.89 targeta QSAR Local Models Q 2 = 0.76 Selectivity QSAR Local Models Q 2 = 0.68 Actual Actual Docking Score ADMET QSAR Global Models Predicted Multiobjective selection Select Optimal Solutions Actual Multi-dimensional de novo design of drug-like compounds. 2013, De Novo Molecular Design ISBN Validation of Reaction Vectors for de Novo Design. 2011, Library Design, Search Methods, and Applications of Fragment-Based Drug Design. ISBN Knowledge-Based Approach to de-novo Design using Reaction Vectors. 2009, 49 (5), pp J. Chem. Inf. Model.

13 Harnessing creativity, knowledge and experience Augmenting knowledge and creativity with computational techniques Diversity of thought and perspectives Open environment and tools for idea-sharing Multi-disciplinary design teams Creativity, intuition and discussion: yes, and Integrated and fully distributed computational tools for every-day design 12

14 Agenda Introductions and Evotec in brief Creativity, knowledge, experience, and interdisciplinary problem-solving High quality science, scientific execution, process excellence every day Fastest progress on projects, high quality drug candidates 13

15 Excellence in molecular evolution Integrated know-how and process workflows throughout the DMTA cycle Analyse Powerful combination of analysis tools to identify best compounds and track progress against optimisation goals Design Excellent understanding of molecules, molecular interactions and properties in context of project needs Test Rapid, relevant, high-capacity efficacy and non-efficacy testing Make Rapid and efficient synthetic execution enabled by real time monitoring of key metrics (cycle time, work in progress etc.) 14

16 Combining brains and tools to make fewer, better compounds Combining multiple brains, best practice and bytes for better design Probabilistic Design Cycle time Cycle time Oral drug-like CNS MPO QED Ro5 Ro3 Ro4 PFI Framework for Collaboration LE BEI, SEI LLE LELP DEI AEI Rationale is to increase probability of designing drug-like molecules Select appropriate guide depending on the stage of development / target tissue Desktop suite of in-silico tools 15 AEI - Rob Riley, Pat Barton, DDT 2016, 21, p. 72

17 Hit evolution to candidate is a continuum Directed and focused chemistry on problem-solving Goal setting based on Target Product Profile (TPP) Asset criteria defined by project team Changing emphasis over project lifetime Project needs & goals Design against key problems Bases on available data Focus on liabilities to be addressed Monitor progress towards achieving project goals Telemetry of project data over time Comparison of series allowing effective prioritisation Based on guiding principles for design Assessing scope to manipulate structure & properties Influenced by project context (e.g. Fast Follower, Structure based, Fragment based, Phenotypic) Focus on problems to solve Gap analysis Molecular tactics to close gaps & address problems Iterative cycle until goals are met 16

18 Key tactics for multi-parameter improvement Directed and focused chemistry for rapid improvement of profiles Establishing the Pharmacophore Determine which molecular features are driving or limiting potency Evolution of molecular scaffolds using series hybridisation and computational scaffold hopping approaches Understanding Conformation Assessing conformational landscape of hit series Exploration of molecular features limiting conformational freedom and assessing their impact on biological profile Focus on Properties Focus on aligning molecular properties of a series with desirable property space 1) Establish independence between trends in molecular properties and biological profile Ensuring Compound Efficiency Hypothesis driven, iterative approach to compound design Preparing minimum number of compounds required to address an issue or assess potential of a series Cycle time 17 1) Desirable property space depends on route of admin, target organ etc

19 Speed of make phase is key for fast progress Tools for real time monitoring of synthetic execution Central data repository of synthesis targets Real time monitoring Snapshot Q ~5200 completed targets across 30 projects Median synthesis time of 8 days 57% of targets completed within 14 days Other indicators available from database Eg WIP across team members Synthesis Cycle time Synthesis Outcome 18

20 Agenda Introductions and Evotec in brief Creativity, knowledge, experience, and interdisciplinary problem-solving High-quality science, scientific execution, process excellence every day Fastest progress on projects, high-quality drug candidates 19

21 Checking progress through visualisation Tools for efficient evaluation of project data Project data warehouse Graphical Analysis Tools Standard views including project telemetry, MPO scoring functions, LipE and AEI plots Efficient data analysis to identify best compounds and track progress against optimisation goals MPO Telemetry Plot LipE Plot AEI Plot (logp/tpsa) AEI 20 AEI - Rob Riley, Pat Barton, DDT 2016, 21, p. 72

22 Problem-solving from Hit to IND Case Study of MPO and innovation in peptidic GPCR project measured LogD (HPLC) (2) LO Entry Conformational twist IC 50 = 16 nm LLE = 5.6; AEI = 4.4 (1) HTS Hit HTS Hit IC 50 = 205 nm LLE = 4.9; AEI = 2.7 Challenging peptidic GPCR target Clinical programs failed due to compound-related DMPK / toxicity issues 1. Selected HTS hits with low LogD / desirable structure MPO (potency, sol, efflux, Ames, PXR/CYP & PK) performed 2. Conformational twist / rigidification provided solubility & potency boost Improved PK and robust efficacy Provided clear IP space human pic 50 21

23 Problem-solving from Hit to IND Case Study of MPO and innovation in peptidic GPCR project measured LogD (HPLC) (3) Ames -Ve EWG for Ames IC 50 = 3 nm LLE = 6.3; AEI = 5.3 (4) Lower Efflux IC 50 = 209nM LLE = 4.9; AEI = 5 (2) LO Entry Conformational twist IC 50 = 16 nm LLE = 5.6; AEI = 4.4 (1) HTS Hit HTS Hit IC 50 = 205 nm LLE = 4.9; AEI = Ames QSAR and nitrenium ion stability models utilised EWG destabilises nitrenium ion formation, protecting against Ames mutagenicity human pic Re-visited isostere - now tolerated (3) solubility, transporter interactions and improves PK 22

24 Problem-solving from Hit to IND Case Study of MPO and innovation in peptidic GPCR project (2) LO Entry measured LogD (HPLC) (3) Ames -Ve EWG for Ames IC 50 = 3 nm LLE = 6.3; AEI = 5.3 (5) Candidate MPO complete IC 50 = 6 nm LLE = 6.2; AEI = 7.0 (4) Lower Efflux IC 50 = 209nM LLE = 4.9; AEI = 5 Conformational twist IC 50 = 16 nm LLE = 5.6; AEI = 4.4 (1) HTS Hit HTS Hit IC 50 = 205 nm LLE = 4.9; AEI = Applying MPO / SAR knowledge provided Candidate (5) D2M studies supported selection and award of PDC IND-enabling studies ongoing human pic PDC = Preclinical development candidate

25 Rapid decision-making on multiple series drives progress Quantifying, visualizing, and monitoring project progress 1 st Candidate MPO scores comprised of: Potency Solubility Protein binding Metabolic stability LogD 24

26 Blending human creativity, knowledge, science and process for better drug discovery Better outcomes when five key features are successfully blended together Human creativity, insight, intuition, inspiration Drug discovery is still a very organic and human endeavor through true teamwork and partnership Extensive knowledge, experience, expertise, know-how Knowledge of analogous problems enables rapid solutions and anticipation and avoidance of problems Blended together, leads to: Faster progress towards Better quality drug candidates with higher probability of success through development At lower costs for partners Multi-disciplinary awareness and close interactions Toughest problems are at the interface between disciplines Highest quality science thinking and tools Relevant, high capacity test systems, computational/predictive tools High performance processes The right, well-designed experiment, the diligently designed compound, executed rapidly, right first time 25

27 High-quality partnerships Testimonials from some of our current partners UCB engages Evotec colleagues on full scale sharing data, goals and objectives just like UCB internal employees would. I have worked with numerous CROs in the past - Evotec is among the best in terms of responsiveness, scientific quality and local management. If you are looking for a high quality and flexible CRO, I would highly recommend Evotec Johnny Zhu, Head of Medicinal Chemistry UK Our research cooperation is a real partnership. We work on every one of our projects in joint teams; both partners have a significant share in their success, Dr. Christoph Huwe, External Innovation Therapeutics at Bayer HealthCare "At the heart of what Exscientia is building is a learning system. Therefore we wanted a partner who fully understood the efficacies that come from a tight design cycle. Evotec is that partner. Prof Andrew Hopkins, CEO Exscientia 26

28 Building innovative drug discovery alliances