day one | day two

Day One25 October 2010 08:25 Chairman's introduction Dr. Peter Richardson, Head of Discovery Research, Cambridge Biotech Limited UK 08:30 Successful Decision Making vs. Corporate Approaches Developing smaller business models to create autonomy - building scientific understanding into decision making processes (Pfizer, GSK) Facilitating decision making champions to achieve drug success What are decision points and how do you maximise costs? Developing a well defined criteria for decision making at all stages of R&D Moving away from the corporate approach to the productivity crisis Making discovery units work - adding senior level expertise and financial resources Does autonomous decision making disconnect research? 09:00 Creative Ways to Address Unmet Medical Needs and Business Demands Addressing unmet clinical needs through collaboration, speed and understanding Success and challenges in the indications discovery effort Developing an indications discovery effort Making a commercially attractive business case Orphan drug development - opportunities for wider indications Dean Welsch, Research Fellow, Indications Discovery, Pfizer Global Research & Development USA 09:30 Strategic Portfolios - Balancing Beteen Small Molecules and Biologics Wisely balancing drug portfolios - evaluating small molecules vs biologics Creating smarter, strategic porfolios Is the grass greener on the biologics side? Have we fully explored the chemical space and the utilities for small molecules? Process improvement in small molecules and biologics New therapeutic approaches Sirna, stem cells and gene therapy Which approaches will lead to an increased productivity? Dr. Neil Weir, Senior Vice President, Global Research, UCB UK 09:35 Target Identification and Validation Derisking targets - using biologically derived information to power small molecule drug design Using antibodies to validate and select targets Obtaining information from therapeutic antibodies to de-risk chemical aspects Connecting the interface between antibodies and new chemical entities Increasing peptide half life Crossing the blood brain barrier Dr. Alastair Lawson, Director of Antibody Biology , UCB SA UK   Lead Identification and Optimisation Med chem and compound management -influence of drug like concepts in early decision making in medicinal chemistry Which drug like properties can better influence early decision making to ensure success? Evaluating early portfolios and becoming compound driven earlier Making decision on where to focus drug discovery processes Probabilistic approaches to filter out poor players and reduce pipeline attrition - extending Lapinsky's rule of 5 Using ligand efficiency metrics Compound management strategies - reducing lypophility and improving safety profiles Dr. Paul Leeson, Director of Medicinal Chemistry, Astra Zeneca UK   Pre-Clinical Development Demonstrate drug advantages early - encourage favourable regulatory responses What do regulators regard as constituting improvement in therapies? Evaluating drug advantages earlier in the process Ensuring me better advantages manifest themselves clearly and effectively How much better does the drug have to be? Addressing and overcoming drug reimbursement issues - achieving favourable responses Are we achieving step wise improvements to get me betters? Formulation strategies, compliance, me betters   Informatics, Data and Knowledge Management Reducing data silo’s to improve decision making in discovery and development Integrating data from biology, chemistry and pre-clinical development to provide a clear understanding of project development Allowing effective decision making based on data from across the R&D disciplines Facilitating a project-team based approach to drug discovery by providing access to clear, annotated data   10:15 New Targets in Inflammation and Metabolic Disorders Merck Invited and MDM, Addex New discovery tools to identify negative allosteric modulators of Tumor Necrosis Factor-Receptor 1 (TNF-R1), an important therapeutic target in rheumatoid arthritis (RA) and other inflammatory diseases Using proprietary platforms Identifying primary hits   Candidate Development Strategies Have we fully explored the chemical space and utilities for small molecules? Exploring new and promising avenues Directing explorations of chemical space towards compounds with the greatest biological relevance Exploring novel chemical space with computational and structural biology Expanding druggable chemical landscapes including target space historically perceived as undruggable Virtual screening partnered with structural biology - X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and/or rigorous homology modeling Cheaper, streamlined ways to identify hits and validating leads prior to preclinical and clinical evaluation Alan C Rigby, Professor of Medicine,Director, Program in Drug Discovery and Target Validation, Harvard Medical School USA Dr. Barry Morgan, Vice President, Molecular Discovery Research, GlaxoSmithKline USA   External Collaboration for Pre-Clinical Development Creating smaller decision making groups and network alliances Breaking down decision making groups Creating different skills and tensions Establishing a network of alliances - emulating small, innovative biotech companies Building and establishing networks Dr. Andrew Parsons, VP Pre-clinical Development, CEED, GSK UK   Improving Decision Making With Effective Data Management Monitoring progress towards R&D milestones with access to clear, annotated data Targeted analysis of data to improve understanding of the disease model and the interaction of candidate compounds Making the best decision for compounds and targets to progress, and those to put on-hold Taking a more holistic approach to decision making in pharma   10:55 Pre-scheduled one-to-one meetings 11:25 New Target Identification Strategies Fully understand new pathways, indications and novel targets with knowledge and literature mining strategies Sourcing data and scientific knowledge and connecting the dots Understanding potential and finding novel targets Repositioning strategies Dr. Jinghai Xu, Director, Knowledge Discovery & Knowledge Management, Merck USA   Small Molecules and Biologics vs. Sirna, Stem Cells and Gene Therapy Which approach will lead to increased productivities? How can the industry further develop new therapeutic approaches? Balancing between pure outright disruptive technologies and novelty vs. sticking to well proven strategies   Better Pathophysiological Disease Models to Improve Tox Studies Increasing predictivity in toxicological studies Understanding the pathophsiology of human disease states and translating this to animal models Improving the relevance of animal models in pre-clincial toxicology studies Enhancing the chances of successfully predicting clinical adverse effects during pre-clinical development   Constructing Open-Access Research Platforms Integrating human biological networks, predictive computational network models, and annotated information on human disease Sharing data whilst retaining competitive advantage and patent positions Linking academic research, public data libraries and pharmaceutical research to improve success in the drug discovery process Developing a better understanding of disease for patient benefit – a philanthropic approach to drug discovery   12:00 Spectacular targets for orphan diseases and larger patient populations Identifying spectacular targets for orphan disease and larger patient populations Understanding how a chain of genes may be the root of several diseases Ensuring rock solid biochemical rationale at the onset - maximising opportunities for extra indications Identifying molecular similarities and pathways between different diseases Quicker, cheaper innovative new drugs - presenting a commercially attractive business case for parallel drug development Developing valuable antibodies and small molecule drugs Risk reward ratio's - achieving cheaper regulatory filings and extra revenue through repositioning strategies Dr. Georg C. Terstappen, Vice President Discovery Research, Siena Biotech SpA Italy   Transforming Fragments into Candidates Unlocking medicinal chemistry innovation - advancing fragment hits to bona fide leads and drug candidates Identifying initial chemistry starting points for drug discovery programs How does a good fragment hit look? Identifying and validating the most advanceable fragment hits Hit detection, evaluating hit quality and methods to evolve fragments towards drug-like leads Identifying and transforming low molecular weight fragments into higher molecular weight drug candidates Opportunities in fragment hits vs. conventional HTS hits? FBDD as an enabling technology for imaginative medicinal chemists - entering a new chemical or IP space   Correlating Animal and in Vitro Toxicity Data Facilitating decision making in pre-clinical development Utilising in vitro data to minimise and refine animal testing – selecting the best NCE’s for testing in the right models Supporting in vitro toxicity screening with validated and scientifically relevant animal tests   Advancing Drug Discovery Processes with Workflow Technology Integrating diverse resources - facilitating knowledge exchange across drug discovery and development disciplines Creating a user-friendly, interactive platform to engage non-programmers and enhance scientific decision making Accelerating the drug discovery process and providing a basis for in silico experiments of the future Developing a more patient focussed drug discovery process through better understanding of disease and patients   12:45 Networking lunch 14:00 Phasing Risk Earlier in Target Identification and Validation Considering pre-clinical safety during target identification Accurate and efficient methods of target identification and validation to address safety and efficacy earlier in the process   Research Alliances and Collaborations Successful lead generation with lucrative research alliances - setting up lean collaborations with biotech and small molecule players Agreeing early licensing deals - sharing risks and rewards Offering free capacity to partners to develop pre-clinical candidate status and developing early alliances Harnessing complementary skills Taking over lead candidates in and at a later stage develop in return for milestone royalties. Expanding therapeutic focus and smarter combination for drugs increase likelihood for investment returns Dr. Mathias Schmidt, Associate Principal, Head of Early Alliance Team, Nycomed GmbH   Species Selection for Biologic Drug Safety Assessment Extrapolating human effects from animal models The importance of genotype similarities between drug targets in humans and model species Predicting organ based toxicity and adverse pharmacological effects resulting from on-target effects Strategies for predicting immunogenicity in animal models – can they be representative of human immune responses?   Using Semantic Web Technologies in Drug Discovery and Development Bridging knowledge gaps in drug discovery Developing tools to access and analyse disparate data sets Combining data from multiple sources in to a single integrated knowledge base through semantic technology   14:30 Pre-scheduled one-to-one meetings 16:15 Bioinformatics and Target Identification Workshop Bioinformatics approaches to target identification ‘Network-reconstruction’ methods to understand the regulatory circuit among genes, proteins and metabolites   Virtual Screening Workshop Virtual high throughput screening to accelerate lead identification and optimisation Optimising the compound library for HTS through in silico modelling - reducing time and resources needed for HTS Improving docking and in silico screening models to improve accuracy of HTS Can virtual screening replace HTS as the standard method of candidate selection? virtual screening, structural biology, X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and rigorous homology modeling   Predictive Toxicology Workshop In silico approaches for early toxicity prediction Meeting regulatory and ICH guidelines utilising in silico approaches to toxicity studies Enhancing lab based toxicity with in silico approaches – reducing the quantity and improving the quality of the studies required Predicting idiosyncratic toxicity through modelling of patient populations – genomic based approaches   Interactive Workshop Cognizant Workshop   17:15 Identifying Winning targets for Therapeutic Intervention Fully exploring pathways -identifying the best target for therapeutic intervention Successfully focusing the drug target selection process to increase future product success Knowledge and decision support technologies to enable rigorous and effective business decision processes Controlling costs in drug discovery and development. Using information management for successful target selection   Carving out a Hit to Lead Position Hit to lead success - improving hit to lead processes Increasing certainty in bioassay results in order to “pass” or “fail” compounds faster Submitting high purity compounds Avoiding false hits from reaction by-products and skewed bioass Increasing productivity in early drug discovery - decreasing attrition in later pipeline stages Using flash chromatography to purify reaction mixtures into potential hits and impurities   Toxicity Predictions for Biologics vs. Small Molecules In vitro assay development for biologic testing – differences in regulatory requirements for safety testing of biotherapeutics Immunogenecity as a critical issue in biologic toxicity Structuring toxicology departments – can biologic and small molecule toxicity screening be carried out side by side, or are they a different discipline?   Informatics tools for long-range planning and portfolio management Ensuring efficient information flow between groups and senior management Managing scale and structure of information during company growth Predicting future portfolio growth and attrition to manage projects and improve decision making   18:45 Chairman's closing remarks and drinks reception

day one | day two

Day Two26 October 2010 08:25 Chairman's opening remarks Dr. Peter Richardson, Head of Discovery Research, Cambridge Biotech Limited UK 08:30 Stimulating drug innovation Dr. Youseff Bennani, VP Drug Innovation, Vertex Pharmaceuticals USA 09:00 Continuous Improvement and Systems Biology Dr. Andrew Seddon, Senior Director Strategic Managment Group, Pfizer Global Research & Development USA 09:30 Drug Repositioning Strategies 10:05 Target Identification and Validation Improving accuracy and efficiency in target identification and validation Improving processes to eliminate bottlenecks in drug discovery and development Using automation technologies and enhancing data reliability Improving data analysis Accelerating drug discovery   Lead Identification and Optimisation Process improvement in small molecules and biologics Encoded library technology: a new approach to lead discovery Translational studies for development of monoclonal antibodies - from discovery to the clinic   Pre-Clinical Development Controlling quality and phasing development risks earlier Earlier decision making during the development pathway Becoming more selective on investment decisions Decision making and awareness - successfully evaluating risks Approaching risk and evaluating portfolio Successfully managing activities going forward Understanding how to phase investment   Informatics, Data and Knowledge Management Reducing data silo’s to improve decision making in discovery and development Integrating data from biology, chemistry and pre-clinical development to provide a clear understanding of project development Allowing effective decision making based on data from across the R&D disciplines Facilitating a project-team based approach to drug discovery by providing access to clear, annotated data   10:40 Morning refreshements 11:00 Target Discovery from Data Mining Approaches High-throughput proteomics and chemical genomics, proteomic data mining and chemogenomic data mining (Havard Medical School) Data mining to fuel target discovery in the post-genomics era Reviewing data mining approaches and its application to target discovery Text and microarray data analysis Emerging approaches - chemogenomic and proteomic data mining Threats - database integration, data quality, annotation, heterogeneity and performance of analytical and mining tools Integrating various data sources for target discovery - text mining and high-throughput data analysis and integrated mining with pathway databases   Early Integration of PKPD Reasoning for Optimal Development of Lead Compounds Making PKPD integration essential for target validation, lead generation and lead optimisation and scaling these to human Using PKPD collaborations to improve planning, execution and evaluation of experiments in primary and safety pharmacology Designing target validation studies Design and data ‘pruning’ of PKPD studies in lead optimisation Analysing data with marginal and substantial temporal (time) differences between exposure and response Designing safety pharmacology studies, assessment of safety margin Making PKPD awareness a vital component in relating preclinical results to acute and long term consequences in humans   Genotox Impurities Addressing the scrutiny on potentially mutagenic impurities · Overcoming regulatory constraints Understanding European and US regulations Dr David Lathbury, Director of Process Chemistry, AstraZeneca UK   Open-Access Data - Facilitating the Future of Pharma R&D Balancing competiveness and benefiting from collaboration through data sharing next steps in collaborative pharma – developing partnerships to share data and knowledge Cultural changes required to facilitate, but control, information sharing Role of the ‘Innovative Medicines Initiative’ in facilitating pre-competitive informatics projects   11:40 Finding Druggable Targets Using functional genomics, proteomics and bioinformatics to expand targets and the druggable genome Defining and contrasting drug-like molecules, druggable targets, and disease-related pathways Discovering new gene targets Letting targets determine compound acquisition strategy Whole-genome analysis of novel druggable targets   Lead Optimisation: Designing the Best Molecules to Move Forward Creating molecules of lead-like and drug-like properties. Shifting to smaller libraries targeted with greater computational sophistication according smarter target-drug premises. Targeting the right drug-like lead generation library - exploiting the information advantage of the chemical genomics approach Develop efficient lead generation capabilities to gain competitive advantage in the drug discovery   Integrating Tox Studies Earlier in Discovery Overcoming the barrier between discovery and pre-clinical development Measuring compound selectivity as a predictor of toxicity and adverse pharmacology Identifying toxicology related to off-target effects during the lead generation process Screening for binding partners and predicting the consequences of off-target binding with chemoproteomic approaches   Systems biology approaches to drug discovery and development A new perspective on complex interactions in biological systems Applications in target identification and toxicity screening Integrated analysis of mining, modelling, manipulation and measurement data Complementing lab-based R&D approaches   12:20 Target Identification and Biomarkers Workshop Using Human tissues in vitro to drive target validation, decisions and progressing best targets Validation human targets and biomarkers - selecting those with the Best chance of clinical success Accelerating development Reduce the risk of late stage failures Improving productivity   Computer Aided Drug Design Workshop Predicting pharmacological activity in silico to reduce animal testing vs. classical approaches to drug discovery In silico modelling of drug – target interactions for successful prediction of pharmacologically active compounds Reducing the burden on the chemistry department by reducing the number of compounds that must be synthesised for screening Successfully identifying weakly binding drugs or inactive drugs at an early stage to remove them from further studies   Cheminformatics Workshop Workshop: Using chemical informatics to organise, analyse Using information systems to predict properties of chemical substances Assisting in the development of novel compounds, materials and processes   ELN Workshop Implementing an ELN system to integrate data and manage decison making in R&D Financial and operational considerations when implementing ELN's Improving data sharing and data security in R&D Improving decision making through facilitating access to data from across disciplines   13:20 Themed luncheon discussions 14:40 Collaboration in target identification/Validation Collaborating with academia and industry with new target identification and validation strategies (Asterand, BMS, AstraZeneca, university of Virginia) Entering into strategic research collaborations Supporting target identification and compound optimisation   Structure based drug discovery Structure based approaches to drug discovery Fragment hit identification Hit validation and lead optimisation strategies Discovering new lead compounds Moving candidates into development   In vitro assay development - improving accuracy in toxicity prediction Improving in vitro assays for predicting idiosyncratic toxicity Meeting guidelines to reduce, replace and refine animal testing Developing disease relevant in vitro assays to improve relevance of in vitro models   Developing an effective data mining system Supporting decision making in drug discovery and development Rapidly categorising and analysing large volumes of information Identifying clear links between documents and concepts - supporting research with published data Predict future behaviour and patterns from analytical data - predicting efficacy and toxicity earlier   15:20 Drug Target Identification/Validation - Bridging Bio- and Cheminformatic Space Producing a target family discovery tool Using bioinformatics for drug target and therapeutic protein identification Bioinformatics to generate a target discovery pipeline using the in silico identification Achieving a greater understanding of the associated chemical space Creating a pharmacology database - bridging target and chemical space Progressing drug discovery from design therapeutics to genomic mining Following high through put genomic technologies at the start of the therapeutic discovery pipeline   Pharmacogenomics and Compound Development Biomarkers and personalised medicine - developing a pre-clinical biomarker plan (J&J) Applying pharmacogenomics approaches to compound development in various therapeutic areas Determining which biomarkers can be used in clinical development to aid in decision making or to help in patient selection Creating subsets of patient populations to gauge how genetic makeup affect their response to specific drugs Analysing samples depending on the disease or drug under study and the clinical issue to be addressed   Predicting idiosyncratic liver toxicity Developing better methods to predict idiosyncratic liver toxicity The role of systems biology, biomarkers and genomics in predicting idiosyncratic toxicity Can this problem be solved during pre-clinical development – encompassing the understanding of the basis of idiosyncratic toxicity in an in vitro assay   Interfacing IT systems Integrating data management systems across departments or across companies during mergers and acquisitions Merging data from different systems to allow cross company access and analysis Overcoming the issue of interoperability between different software Practical integration of IT systems - moving to a unified system for data storage, access and analysis   16:00 Stem Cells in Target Identification and Validation Using stem cell technologies at discovery Stem cells - in vitro technologies as better models to discover drug targets   Biologic Drug Discovery Antibody based drug discovery and development Translational strategies for development of MAB's from discovery to the clinic Monoclonal antibody drug discovery technology   Pre-Clinical Assessment of Cardiac Toxicity – Predicting cardiac effects early in development Developing in vitro methods to predict cardiac toxicity prior to clinical development Addressing the disconnect between the behaviour of cultured cells and cells in situ Utilising differentiated embryonic stem cells as a model system for cardiac toxicity prediction   Internal vs. external data management Considerations when out-sourcing data management Ensuring interoperability with in-house systems for effective data transfer and access Analysing core assets and capabilities – strategic decisions based on value of information Gaining a competitive advantage in a cost-effective way Where to place investment to organise data and support experimental decision making better?   16:30 The Road Ahead for Pharma - Long Term Science and Innovation (Astra Zeneca) Collaborationa and alliances Outsourcing strategies 16:30 Considering New Investment Areas - Neglected Diseases Creating the open lab approach at GSK Malaria 17:00 Worldwide Development and Outsourcing Strategies 17:30 Chairman's closing remarks