Day 1: Toxicology

09:00 - 09:30 Delegate Arrival: Welcome & Networking

09:30 - 09:45 Opening Speech

09:45 - 10:45 Plenary: Toxicology Prediction - The present, the future, the challenges
                          Professor Alan R Boobis,
                          Department of Medicine, Imperial College London
Abstract
In general, current toxicity testing is relatively effective in protecting human health. However, toxicology is undergoing a profound paradigm shift. There are too many chemicals to test using conventional approaches, animal models may not be predictive of all endpoints, combined exposures need to be evaluated and biological knowledge has advanced markedly, all leading to the need for new approaches to toxicity testing.  This will require a new generation of in silico and in vitro methods, where perturbations of toxicity pathways are identified and effects in vivo are predicted using physiologically-based models. Conventional validation will not be appropriate and hence there will need to be agreement on how the tests will be assessed for reliability.  Toxicity testing should be proportionate to the potential degree of concern. More consideration will need to be given to margin of exposure, taking into account relevant human exposure, mode of action and uncertainty.

10:45 - 11:30 The Next Generation of Toxicology Risk Assessment
                          Dr David J Dix,
                          Deputy Director, US Environmental Protection Agency
Abstract
Coming soon.

11:30 - 12:00 Coffee

12:00 - 12:45 New approaches to the prediction of metabolites from the cytochromes                          P450                       
                         Professor Patrik Rydberg,
                         University of Copenhagen
Abstract
The cytochromes P450s are involved in the metabolism of ~90% of all drugs. They are a family of promiscuous enzymes which can metabolize many different compounds leading to multiple products for each drug compound. Prediction of this metabolism has been shown to be tricky at best, however, recent approaches have shown that we can improve the state-of-the-art significantly, using reactivities which have been pre-computed at a very advanced computational level.
No matter how good a method is, the medicinal chemist wants a prediction to make sense, and if a model is interpretable modifications to chemical structure is easier to perform. This talk will introduce a successive model of determining both which cytochrome P450 isoforms contribute to the metabolism of a drug, and what the metabolites will be, all built from chemically sensible information that can be easily understood by the non-expert.

12:45 - 13:45 Buffet Lunch & Poster Session

13:45 - 14:30 Bridging Computational Modelling and Wet-bench Toxicology: Inter-disciplinary                           Approach to Move the Field Forward
                          Professor Ivan Rusyn,
                          UNC Gillings School of Publich Health, University of North Carolina
Abstract
Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity endpoints. The ability to virtually screen tens of thousands of chemical structures for their potential activity or toxicity adds value to the process of candidate selection in drug development or in a search for replacing chemicals in commerce with less hazardous substances. Numerical descriptors representing the chemical structure can be easily calculated for any number of molecules and they have been traditionally used as multi-dimensional data matrix for QSAR model development and application.

While experimentally-derived toxicity data has been difficult to obtain on a large number of chemicals in the past, recent efforts by the Tox21 consortium of the US Federal agencies, and the academic laboratories are generating quantitative in vitro toxicity screening data on hundreds of environmental chemicals in thousands of in vitro experimental systems.

In addition, publicly accessible toxicogenomics data on hundreds of chemicals provides another dimension of the molecular information that is potentially useful for modeling. We posit that a combination of chemical structural information, in vitro screening, and/or toxicogenomics data can be used to generate “hybrid” quantitative models to predict human toxicity and carcinogenicity. Using several case-studies, we illustrate the benefits of a “hybrid” modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage.

14:30 - 15:15 Networking in Toxicity: Modelling of the Toxicity of Small Molecules as an Aid in                           Designing New Drugs
                          Professor Hans Westerhoff,
                          Director, Manchester Centre for Integrative Systems Biology (MCISB)
Abstract
Molecules act in networks before they affect biological function.  Systems Biology examines how and to what the extent the networking determines that function.  The effect of a medicinal drug is determined by its pharmacodynamics, by its direct effect on its molecular target and by the network effect of that target.  We will discuss three issues.  First we will review the development and implementation of a strategy of differential network-based drug targeting.  This strategy puts molecule and network, action and toxicity in the single frame it may deserve.  Then we shall discuss how we implement systems biology to pre-evaluate the performance of proposed biomarkers for glutathione-mediated detoxification. This leads us to propose multi-dimensional biomarking supported by systems pharmacology.  Finally we shall suggest how revolutionary ICT may put the Humpty-Dumpty together again that we have all been taking apart so successfully, in a strategic activity called ITFoM.

15:15 - 15:45 Coffee

15:45 - 16:30 Application of Stem Cell Derived Tissues to Improve Cardiac Safety Assessment
                          Dr Kyle Kolaja
                          Director and Global Head of Predictive Toxicology Screens and Investigative Safety,                           Hoffmann-La Roche
Abstract
Cardiac liabilities are a significant cause of compound attrition. however non-clinical models are often insufficient, relying on animals or cell cultures lacking the full features of cardiomyocytes. In this talk, I'll discuss the development and characterization of a human iPS-derived cardiomyocyte model that is senescent, beats, and expresses key markers seen in cardiomyocytes in an intact heart, including the clinically relevant ion channels. In addition, the extensive validation data from the model for arrhythmia prediction will be presented as will the future implications of stem cell derived cardiomyocytes in clinical drug safety.

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16:30 - 17:15 Application of Transgenic Models in Metabolism and Toxicology
                          Professor Roland Wolf
                          University of Dundee
Abstract
Coming soon.

17:15 - 17:30 Closing remarks & Thanks
                          David Watson
                          CEO, Lhasa Limited

19:00 - 22:00 Dinner & After Dinner Speech
                          Toxicity - A View From Outside
                          Professor Hugo Kubyini
                          Retired Professor, BASF AG and University of Heidelberg

Abstract

“Toxicity” results from a multitude of different physiological mechanisms, drug toxicity may either come from a direct effect on a certain biological target (e.g. hERG channel inhibition), from the chemical reactivity of the xenobiotic or its various metabolites, from CYP inhibition or CYP induction, or from any other drug-drug or food-drug interactions. In addition, genetic variability may be a reason for unexpected toxic effects. This results in various problems in the prediction of toxicity and the extrapolation of human toxicity from animal studies also poses unexpected surprises. In the past, most drug failures in (late) clinical studies resulted from a lack of efficacy or toxicity – two reasons which are to some extent interrelated: if doses are too low, there may be no effect, if doses are too high, toxicity is observed.

  Day 2: Systems Approaches

08:30 - 09:30 Plenary: Emerging Areas in Toxicity Prediction
                          Professor Kevin Park,
                          Director of the M.R.C. Centre for Drug Safety Science and Head of the Institute of                           Translational Medicine, University of Liverpool
Abstract
Adverse Drug Reactions (ADRs) are public health concern because of the prevalence of such reactions in the clinic where they can prohibit effective therapy and because they are an impediment to the development of new medicines. The remit of the MRC Centre for Drug Safety is to understand the mechanisms of Adverse Drug Reactions in man and our philosophy is to study them from man to molecule and back again. The Centre has set out to foster non-competitive research, between academia, the pharmaceutical industry and drug regulation through the provision of focused workshops and by acting as a focus for national and international multi-centre collaborations. There is a need to understand mechanisms of adverse drug reactions in order to inform basic and clinical science which in turn can be used to inform, the clinician, the patient, the drug discovery process, and drug regulation. It is also important to communicate to the public what is and is not feasible i.e. to attune public expectation to the reality of the science. The simplest classification of ADRs is:

• on target: exaggerated pharmacological response which can be avoided by prescribing the right dose of the right drug to the right patient

• off target: not related to primary or secondary pharmacology and include idiosyncratic reactions It is now clear that frequency and intensity of a particular ADR is a function of both chemical liabilities in the drug molecule and the phenotype and genotype of the patient. We have therefore developed experimental approaches which involve triangulation between clinical studies, in vitro models and in vivo models. Such investigations are underpinned by clinical analysis, genetic analysis, novel biomarkers, novel model systems and DMPK analysis. The ultimate aim is to inform a) personalised medicines and b) comparative pharmacology & toxicology. Warfarin is a paradigm in clinical pharmacology for the study of on target toxicity: bleeding. We now have a full and integrated knowledge of the molecular pharmacology and molecular toxicology. Such information is used to predict and prevent ADRs arising from drug interactions and inter-patient variation in genotype. Such knowledge has also informed the design novel anticoagulants such as thrombin inhibitors. Off-target toxicity can arise with any class of therapeutic agent and can affect any system in the body. Such ADRs may not be predictable, or indeed reproducible in either in vitro or animal models. ADRs can demonstrate marked individual susceptibility (idiosyncrasy) and can be serious (life-threatening) when the innate or adaptive immune system is involved. Chemical stress is thought to be a key initiating factor for off-target drug-induced toxicity. However, although chemical liabilities can be identified an early stage in drug discovery there is presently no means available to assess human risk until the drug is in clinic use. Therefore a better understanding of the biological consequences of chemical stress is required which in turn requires the need for novel experimental systems that have defined relevance to processes that actually occur in man and novel biomarkers can used universally in in vitro models, relevant animal models and in man. Studies with model compounds and drugs such as paracetamol (acetaminophen), piperacillin, bleomycin and aminoglycosides have helped to define the response of target organs to chemical stress to various biological outcomes. These include adaptation (cell defence), apoptosis, necrosis, inflammation and activation of the innate and adaptive immune systems. Complementary genetic analysis in patients can provide insight into individual susceptibility to serious ADRs, particularly those of an immunological nature.

09:30 - 10:15 Systems Biology in Toxicology
                          Professor Steve Oliver,
                          Director of Cambridge Systems Biology Centre, University of Cambridge
Abstract
Coming soon.

10:15 - 10:45 Coffee

10:45 - 11:30 Translation of In Silico to In Vitro to In Vivo in Toxicity Prediction
                          Dr Harvey Clewell,
                          The Hamner Institute for Health Sciences, USA
Abstract
In the field of toxicology and chemical risk assessment, there is a special focus and interest on the development, validation and acceptance of methods which could reduce, refine or replace the use of laboratory animals in the assessment of the toxicity of chemicals. In the absence of in vivo data, a first step could be the use of in silico predictions of metabolism and toxicity. The outcome could be used to prioritize in vitro test systems. Here we compare the predictions of several toxicity prediction software systems with the observed in vivo toxicity, to investigate to what extent they can be correctly predicted. For the evaluation of these systems, a set of widely varying chemicals was selected based on the availability of in vivo data.  Additionally, in silico predicted metabolites of the chemicals of interest were compared with observed in vivo metabolite formation. Subsequently, the predicted metabolites were included in the toxicity predictions.

11:30 - 12:15 Transporters in Drug Safety
                          Professor Yuichi Sugiyami,
                         RIKEN (The Institute of Physical and Chemical Research), Japan
Abstract
Drug transporters are expressed in many tissues, such as the intestine, liver, kidney and the brain, and play key roles in drug absorption, distribution and excretion.This presentation will summarise the significant role played by drug transporters in drug disposition, focusing particularly on their potential use during the drug discovery and development process. The use of transporter function offers the possibility of delivering a drug to the target organ, avoiding distribution to other organs (thereby reducing the chance of toxic side-effects), controlling the elimination process, and/or improving oral bioavailability. It is useful to select a lead compound that may or may not interact with transporters, depending on whether such an interaction is desirable. The expression system of transporters is an efficient tool for screening the activity of individual transport processes. The changes in pharmacokinetics due to genetic polymorphisms and drug-drug interactions involving transporters can often have a direct and adverse effect on the therapeutic safety and efficacy of many important drugs.
 For drugs, the target molecule of which is inside the cells, the efflux transporter is the determinant for their pharmacological effect or adverse reactions even though it had negligible impact in the plasma concentrations.  Because of difficulty in quantitative evaluation of the subsequent efflux process, the transporters playing key roles in the efflux process remains unclear in humans.  Development of probe substrates applicable to the PET imaging will elucidate the quantitative relationship between the transport activities and drug response.  Drug transporters are also important for the disposition of endogenous and food derived compounds.  Metabonomic analysis has succeeded identifying such compounds both in animals and human, which could be a good biomarker for the transporter function in vivo.

12:15 - 13:15 Lunch

13:15 - 14:00 Predicting Drug-Drug Interactions
                          Professor Geoff Tucker,
                          Emeritus Professor of Clinical Pathology, University of Sheffield
Abstract

The prediction of the extent of metabolically-based drug-drug interactions from in vitro data has become a significant issue in drug development. Retrospective studies often question the reliability of such extrapolation. However, the quality of the output always reflects the quality of the input, and it is essential that the complexities associated with the exercise are acknowledged fully and incorporated, where possible, into the algorithm. For example, factors that are not always allowed for include – the role of the intestine in ‘first-pass’ metabolism; the different concentrations encountered by enzymes on ‘first-pass’ and re-circulation; non-specific microsomal binding; correct numbers for microsomal protein per gram of liver and hepatocellularity; the interplay between transporters and enzymes; mechanism-based inhibition; simultaneous enzyme inhibition and induction; inhibitory metabolites; and important features of the experimental design of the in vivo study that is being simulated. In addition, it is vital to predict outcomes in virtual populations, not just the non-existent ‘average patient’, if individual patients at the extreme of risk are to be identified. By simulating a relevant patient population, incorporating a broad range of demographic, physiological, genetic, enzyme abundance values etc, the exercise can provide early warning of the complex mix of patient characteristics predisposing to risk.

The Pharmacogenomics Knowledge Base (PharmGKB) is a comprehensive resource that curates knowledge about the impact of genetic variation on drug response. Genes and genetic variations that are most important for drug response (many directly linked to drug efficacy and toxicity) are catalogued and presented in the form of drug-centered pathway diagrams and Very Important Pharmacogene (VIP gene) summaries.  As the field advances, our focus has shifted towards facilitating clinical implementation of pharmacogenomics discoveries. The PharmGKB now highlights clinical information including genotype-guided dosing guidelines, drug labels, genetic tests, and potentially clinically actionable gene-drug associations as well as genotype-phenotype relationships. We will present examples such as how to find information on established pharmacogenomics biomarkers for drug-induced toxicity (e.g., HLA B*5701 for avoiding abacavir-related hypersensitivity syndrome) and how to generate hypotheses in predictive studies to understand the genetic basis behind variable drug response and toxicity.  The PharmGKB is freely available at http://www.pharmgkb.org/.

Signaling and metabolic pathways acting within and between cells in an organism may be considered as integrated circuits working to maintain cell growth or homeostasis based on inputs from external influences and other, connected pathways. The components of these circuits comprise DNA, RNA, proteins, enzymatic activities, small molecules, ions etc., and in order to fully understand the circuit, or to “reconstruct the system” it is necessary to consider all of it’s components as well as the connections (interactions) between them. These concepts are the basis of the systems biology approach to biological pathway analysis and network reconstruction. In recent years this approach has been successfully used to integrate data of different types, and from different sources, on multiple types of circuit component – genes, mRNA, proteins, metabolites, microRNA, to obtain a more precise and comprehensive understanding of how disruptions to the circuitry can lead to disease or toxicity. Gross damage to the circuitry by removal or functional impairment of certain components may impact the functioning of the circuit. Individual differences in the system, arising through sequence variations in the DNA template for individual components, also may affect the response of the circuit to normal stimuli or to xenobiotic interference. These variations manifest as different susceptibilities to disease, responses to therapeutic intervention or risks of chemical toxicity. The integration of data on the functional consequences of sequence variation to the systems biology circuit model will be critical to complete understanding of system malfunction or failure in disease or toxicity, and to the successful implementation of personalized medicine.