DMP-header

- 药物代谢和药物动力学优化 -

Lead compounds in drug discovery need to be optimized for both efficacy and safety. Unfortunately, some of the adverse events related to drug metabolism, transport, drug-drug interactions and drug clearance do not surface until much later in development. Improvements in cell-based assays, new predictive models for in vitro and in silico testing and the emphasis on fail fast, fail early has driven the need for more efficient and effective ADME testing. Cambridge Healthtech Institute's Inaugural Optimizing Drug Metabolism & Pharmacokinetics conference, will bring together experts from ADME, DMPK, PKPD, safety pharmacology and toxicology groups to talk about some of the issues that must be considered right from lead optimization through early dosing in humans. The talks and discussions will cover what's new and relevant in ADME and PKPD assessments using relevant case studies, research findings, and highlighting use of innovative assays and technologies.

Who should attend: Students, post-docs, lab technicians, managers, scientists, team leads, directors and executives from pharma/biotech, academia, government, contract research labs and technology companies involved in discovery chemistry, drug design, ADME/PKPD/DMPK, high-throughput screening, systems/safety pharmacology, toxicology and other areas of lead identification and optimization.


Final Agenda

Tuesday, June 19

7:30 am Registration Open and Morning Coffee

ACCURATELY ASSESSING DRUG BINDING, DISTRIBUTION AND PENETRANCE

8:15 Chairperson's Opening Remarks

John Reilly, PhD, Senior Research Investigator, Global Chemistry, Novartis

8:20 Determination of Free Fraction of Highly Bound Drugs in Plasma

Zhengyin Yan, PhD, Senior Scientist, Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc.

Equilibrium dialysis has been widely used in plasma protein binding studies to measure the fraction of drug unbound (fu), an important pharmacokinetic parameter for both dose projection and drug-drug interaction (DDI) prediction. However, there has been a shared concern over the accuracy of fu values for highly bound compounds and current guidelines arbitrarily cap the lower limit of fu values at 0.01 to avoid potential false negatives in DDI prediction. A simple strategy is proposed to reliably measure fu values and ensure true equilibrium attained for high binders.

8:50 Intracellular Unbound Drug Concentrations in Presence of Metabolism and Transport

Priyanka Kulkarni, PhD, Scientist, Pharmacokinetics and Drug Metabolism, Amgen, Inc.

Accurate prediction of target activity of a drug and rational design of dosing regimen requires knowledge of drug concentration at the target. Liver perfusion experiments in rats along with modeling and simulation techniques were used to model the unbound intracellular drug concentrations and characterize the differential effect of metabolism and transport on the same. Together, these results support the use of compartmental modeling to predict intracellular concentrations in dynamic organ-based systems.

9:20 Assessing Drug Distribution and Penetration in Tumor Xenografts, Liver and Bladder in Intact, Live Animals

Margarida Barroso, PhD, Associate Professor, Department of Molecular and Cellular Physiology, Albany Medical College

Macroscopic Fluorescence Lifetime Imaging of Forster Resonance Energy Transfer (MFLI-FRET) provides longitudinal quantitative measurements of target engagement of protein-drug or antibody-drug conjugates in liver, tumor and bladder in live and intact animals. MFLI-FRET is poised to become an analytical technique of choice to measure target engagement in critical organs associated with targeted drug penetration and delivery efficiency as well as drug toxicity and clearance.

9:50 Grand Opening Coffee Break in the Exhibit Hall with Poster Viewing

10:35 Can Off-Target Promiscuity Be Predicted by a Simple LC Analysis?

John Reilly, PhD, Senior Research Investigator, Global Chemistry, Novartis

Drug accumulation and off-target promiscuity has been shown to be able to be predicted by a simple phospholipid-affinity measurement by a HPLC affinity measurement. The presentation demonstrates that phospholipid affinity measurements can more accurately predict "Tissue to Plasma" ratios and off-target promiscuity hit rates. In addition, prediction of non-specific binding can also be predicted by using these measurements. Case example studies will be presented.

11:05 DMPK Strategies and Challenges for Colon Targeted Drug Delivery of Small Molecules

David Duignan, PhD, Principal Research Scientist, Drug Metabolism, Pharmacokinetics & Bioanalysis, AbbVie Bioresearch Center

 Metabolon Logo  11:35 Presentation to be Announced 

 

 12:05 pm Session Break

12:10 Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

12:40 Session Break

OPTIMIZING EARLY DRUG DOSING

1:15 Chairperson's Remarks

Ganesh Rajaraman, PhD MBA, Associate Director, DMPK, Celgene Corporation

1:20 An Integrated Discovery Rank Dose Approach for an Optimal Balance of Properties to Progress Compounds

Ganesh Rajaraman, PhD, MBA, Associate Director, DMPK, Celgene Corporation

For oral drugs, delivering a candidate with low efficacious dose is the primary objective. Based on designated cut-off values from in vitro screens, compounds are funneled down but without guidelines as to how each property impacts dose estimation at the early stage. The talk aims at integrating properties to calculate efficacious doses to rank order compounds for an optimal balance rather than individual cut-offs.

1:50 Strategy for CYP3A Induction Risk Assessment from Preclinical Signal to Human: Case Study of a Late-Stage Discovery Compound

Jialin Mao, PhD, Senior Scientist, DMPK, Genentech

The exposure of Comp X decreased by four-fold at oral doses of 100 mg/kg twice daily for seven days in cynomolgus monkeys. Additional in vitro and PBPK work was conducted to understand: (1) the causes for the significant reduction in monkeys, (2) the extrapolation of in vitro induction data to in vivo findings in monkeys, and (3) the relevance of this pre-clinical finding to humans at the projected human efficacious dose.

2:20 A Pharmacokinetic/Pharmacodynamic(PK/PD)-Based Approach to Lead Optimisation in Drug Discovery Programs

Ramesh Jayaraman, CSO, TheraIndx Lifesciences Pvt Ltd

In preclinical drug discovery, emphasis is based on potency and pharmacokinetics (PK) to optimize candidates while less attention is given to linking of PK to pharmacodynamics (PD) effects - onset, intensity and duration of pharmacological effect. Early characterization of PK/PD helps in selecting compounds with optimum properties for progression to advanced stages. This talk will discuss the applications of PK/PD combined approach to optimize candidates.

2:35 Sponsored Presentation (Opportunity Available)

2:50 Refreshment Break in the Exhibit Hall with Poster Viewing

USING MODEL-BASED STRATEGIES FOR BETTER IN VITRO TO IN VIVO TRANSLATION

3:30 Drug Development Using QSP Modeling and Its Application to Oncology and Immunology

Rangaraj Narayanan, PhD, Director, Drug Metabolism and Pharmacokinetics, Shire Pharmaceuticals

4:00 Assessment of Transporter Mediated DDI for Compound X Using PBPK Modeling

Yuan Chen, PhD, Principal Scientist, DMPK, Genentech

PBPK modeling-based prediction of transporter-mediated DDI is a growing area that can benefit clinical candidate selection and early development in humans. Compound X is a potent inhibitor of OATP1B1/1B3 in vitro. To inform clinical DDI risk, a PBPK model was developed to predict DDI between compound X and OATP substrate pravastatin in humans.

4:30 Machine-Learning Approaches for ADME Optimization

Istvan Enyedy, PhD, Principal Scientist, Medicinal Chemistry, Biogen

Machine learning approaches help us build prediction models based on data we have accumulated. We started using Kriging for efficiently building and maintaining ADMET prediction models that help us doing multiparameter optimization. The predicted probability of a compound to satisfy the required ADMET properties may be useful for prioritizing compounds. Kriging can also estimate the error of the prediction and of the experiment.

5:00 Find Your Table and Meet Your Moderator

5:05 Interactive Breakout Discussion Groups

This session features various discussion groups that are led by a moderator/s who ensures focused conversations around the key issues listed. Attendees choose to join a specific group and the small, informal setting facilitates sharing of ideas and active networking.

Key Issues Related to Drug Transporters in a Pharma R&D Setting

Moderator:

Li Di, PhD, Research Fellow, Pharmacokinetics, Dynamics and Metabolism, Pfizer

  • How can we best generate reliable in vitro transport kinetics and inhibition data?
  • Many transporters do have overlapping substrate-specificity, how can we assess and quantify an individual transporters' contribution?
  • Regulation of transporters (induction, disease, epigenetics) can significantly modulate overall transport capacity. How can this be integrated into current in vitro - in vivo extrapolations?

5:45 Reception in the Exhibit Hall with Poster Viewing

7:00 Close of Day

Wednesday, June 20

7:45 am Registration Open and Morning Coffee

UNDERSTANDING AND PREDICTING DRUG METABOLISM AND TRANSPORT

8:25 Chairperson's Remarks

Li Di, PhD, Research Fellow, Pharmacokinetics, Dynamics and Metabolism, Pfizer

8:30 New Advances in Clearance Prediction with Hepatocytes

Li Di, PhD, Research Fellow, Pharmacokinetics, Dynamics and Metabolism, Pfizer

Significant advances have been made recently to predict clearance of low turnover compounds and clearance involved both enzyme- and transporter-mediated processes. This presentation will discuss novel methods to measure low clearance and a unified approach to predict clearance involved both metabolic and transport mechanisms with cryopreserved hepatocytes.

9:00 Integrated in silico Approach to Predict CYP Inhibitors and Pharmacogenetics Considerations

Maria A. Miteva, PhD, Research Director, Molecules Therapeutiques in silico (MTi), Inserm Institute

Cytochrome P450 (CYP) and its central role in drug metabolism, drug-drug interactions and pharmacogenetics will be discussed. The malfunction of CYP, e.g. due to single nucleotide polymorphism, could lead to decreased drug metabolism causing toxicity, or affected prodrug activation. An integrated structure- and ligand-based in silico approach to predict inhibitors of CYP and to analyse the impact of missense mutations on CYP drug metabolism will be presented.

9:30 Sponsored Presentation (Opportunity Available)

10:00 Coffee Break in the Exhibit Hall with Poster Viewing

DMPK FOR NEW DRUG MODALITIES AND COMBINATION THERAPIES

10:45 Dynamic Drug Combination Analysis Platform for Preclinical to Clinical Translation of Novel Oncology Drug Combinations

Tomoki Yoneyama, PhD, Senior Scientist 1, DMPK, Takeda

The dynamic PK-efficacy model for combinational therapies in oncology was established in mice and translated in humans. The established model provides the means of quantitatively comparing the dynamic combinational antitumor effects of two potential combinational therapies in humans based on mouse experimental data. The model is also powerful for dose regimen optimization.

11:15 DMPK Support for Screening Antibody Drug Conjugates (ADCs)

Ekta Kadakia, MS, Scientist 1, DMPK, Takeda

DMPK support for ADCs focuses not only on characterizing attributes associated with suboptimal pharmacokinetic (PK) behavior, but also on integrating PK, PD (pharmacodynamic) and efficacy data to identify potential ADC drug candidates with the most favorable properties to interact with target-expressing cancer cells. This presentation will discuss the application of different PK and PK/PD-related analysis to inform the selection of ADCs.

11:45 Session Break

11:50 Bridging Luncheon Presentation: Use of a Collaborative Tool to Simplify the Outsourcing of Preclinical Safety Studies

Amanda Benjamin, Head, Alliance and Project Management, Drug Safety and Metabolism, AstraZeneca

Ruth Maclean, Senior Client Manager, Charles River

In 2012, AstraZeneca entered into a strategic relationship with Charles River whereby preclinical safety packages comprising safety pharmacology, toxicology, formulation analysis, in vivo ADME, and pharmacokinetics studies were outsourced. Processes were created to ensure seamless workflows in order to accelerate the delivery of new medicines to patients. This talk explores the preclinical safety outsourcing model and how a collaborative tool helped translate processes into simpler integrated workflows across two companies.

12:20 pm Dessert and Coffee Break in the Exhibit Hall with Poster Viewing


1:00 PLENARY KEYNOTE SESSION

Partnering for Sustainable Funding

The panel is designed to discuss partnering between various stake holders such as drug discovery startups, VC firms, large pharmaceutical companies and academic labs in order to advance new target discovery and preclinical research. VC companies, and pharma search & evaluation departments will be represented on the panel.

Jens Eckstein, PhD, President, SR One

Barbara K. Sosnowski, PhD, Vice President and Global Head, External R&D Innovation, Pharmatherapeutics and WRD External Partnerships, Pfizer, Inc.

Kevin Bitterman, PhD, Partner, Atlas Venture

Vivian Berlin, PhD, Director of Business Development, Life Sciences, Office of Technology Development, Harvard University

Plenary Technology Panel

Advancing Innovation in Drug Discovery and Translational Research

This year's Plenary Technology Panel features a group of technical experts from life science technology and service companies, who share their perspectives on various trends and tools that will likely change the way in which we traditionally approach preclinical drug discovery and development. Attendees will have an opportunity to ask questions and understand the impact of recent technical advances.

Ashley Rae Kark, MBS, Director, Corporate Relations, Scientist.com

Additional Panelists will be Announced

Sponsorship Opportunities Available

2:30 Refreshment Break in the Exhibit Hall with Poster Viewing

3:10 Close of Conference


Recommended Event Package

Short Course 3: Drug Metabolism and Its Impact on Decisions in Lead Discovery and Drug Development

Short Course 10: Applications of Artificial Intelligence & Machine Learning in Drug Discovery & Development

Short Course 15: Evaluating and Characterizing in vitro Models of Drug Toxicity

Conference: Optimizing Drug Metabolism & Pharmacokinetics

Conference: Predicting Drug Toxicity


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* 活动内容有可能不事先告知作更动及调整。