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Presentation 5

Mathematical predictions of cardiac toxicity in human: Advances towards the 3Rs in Safety Pharmacology

Dr Alfonso Bueno-Orovio; University of Oxford

Cardiotoxicity is one of the leading causes of failure during drug development and, more worrying, after

marketing approval. Withdrawal due to cardiotoxicity has increased from 5.1 to 33%, including compounds to

treat cardiovascular problems as well as drugs not intended to affect the heart such as antihistamines. Current

strategies for preclinical screening heavily rely on animal experimentation, yet 20-50% of advanced candidates

have to be abandoned due to adverse outcomes, even late in the drug development process. This has called

into question the reliability of animal-safety testing paradigms and has led to demands for more predictive

human-based tools.

There is an important opportunity to overcome the challenges associated with cardiotoxicity through the use

of in silico models of the human heart. The figures above could be drastically reduced, and at a smaller cost of

animal experimentation, by the adoption of in silico technologies in the earlier phases of the drug development

process. In this talk, I will discuss the maturity of mathematical models for the prediction of cardiac toxicity in

humans, based on their accurate representation of biological processes after more than 50 years of

technological development. Representative examples on the use of such models against retrospective clinical

trials will be presented to further demonstrate the power of these technologies in safety and efficacy decision

making.

Biography

Alfonso obtained an MSc in Industrial Engineering (2002) and a PhD in Physics and Mathematics (2007) on

modelling and simulation of human ventricular electrophysiology from the University of Castilla-La Mancha,

Spain. Since then, Alfonso has held different positions in industry and academia, including his participation in

the EU-funded preDiCT project in drug cardiotoxicity. His research is currently based in the Oxford

Computational Cardiovascular Science team, part of the BHF Centre of Research Excellence, as a Senior

Research Scientist.

Alfonso’s research aims at the development of integrative approaches for cardiovascular research, bridging

clinical and experimental data with modelling and simulation, to improve the understanding of the heart in

health and disease, and to reduce and replace animal experimentation for drug cardiotoxicity. He has played a

central role in the development of predictive methodologies for cardiotoxicity at the population level, and their

translation into friendly software to facilitate their industrial and regulatory uptake. Alfonso is also committed to

dissemination and outreach for the clinical and industrial uptake of in silico medicine, and to supporting the

research community by open access to tools and methodologies.

Mathematical predictions of

cardiac toxicity in humansAdvances towards the 3Rs in Safety Pharmacology

NC3Rs/HESI 2016 Workshop

London, September 14th, 2016

Alfonso Bueno-OrovioComputational Cardiovascular Science Group

Department of Computer Science, University of Oxford

Contact: Alfonso.Bueno@cs.ox.ac.uk

Computational Cardiovascular Science Group, OxfordOliver Britton, Kevin Burrage, Louie Cardone-Noott,Vicente Grau, Aurore Lyon, Héctor Martínez, Ana Mincholé,Anna Muszkiewicz, Elisa Passini, Xin Zhou, Blanca Rodriguez

Cardiovascular Medicine, OxfordRina Ariga, Xing Liu, Barbara Casadei, Hugh Watkins

Jannsen Pharmaceutica, BelgiumHua Rong Lu, Rob Toward, Jutta Rohrbacher, Hermans An,Karel Van Ammel, David Gallacher

Food and Drug Administration, USASara Dutta, David Strauss

University of Szeged, HungaryAndrás Varró, László Virág

Technical University of Dresden, GermanyUrsula Ravens

Universities Politechnical of Valencia and Zaragoza, SpainAlejandro Liberos, Maria Guillem, Andreu Climent,Carlos Sánchez, Esther Pueyo

Acknowledgments

Safety Pharmacology

“Safety pharmacology is the study of the potentialundesirable pharmacodynamic effects of a substance

in relation to dosage within the substance'stherapeutic range and above.

The animal models that are thought to be similar tothe human disease may provide further insight in the

pharmacological action.”https://en.wikipedia.org/wiki/Safety_pharmacology

Animal research in Safety Pharmacology

~400 Investigated New Drug (IND) submissions / year (2013-2015)1

~1,600

/ year

In-vivo QT assay (ICH S7a/S7b guidelines):

Gold standard: telemetered dog ~4 animals/study

~54,000

/ year

Selection of leading compounds:

~1 IND/10 leading compounds ~12-15 animals/study

~480,000

/ year

Contractility assays:

~1 IND/75 early drugs ~16 animals/study

1 http://tinyurl.com/IND-submissions

Still…

Last 25 years, 81 drugs withdrawn from the market (20% due to arrhythmias1).

Attrition due to cardiotoxicity still about 40%.

Source: Pammolli et al., Nat Rev Drug Discov 2011

1 Li et al, Arch Toxicol 2016;90:1803-162 Holmes et al, Nat Rev Drug Discov 2015; 14:585-7

Recent pharmacological “productivity crisis”2:

o calling into question the reliability of preclinical animal testing;

o rising demands for more predictive human tools.

A call for human-based approaches

{Ravens U and Cerbai E. Europace 2008} {Jost et al. J Physiol 2013}

Animal and human hearts are different.

Different balances of currents = different effects ofdrug block.

Integrative physiology through modelling

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CellularElectrophysiology

Tissue Properties MembraneKinetics

ElectricalStimulation

Propagation of the electrical impulse

Adapted from Dr Vincent Jacquemet (Univ. Montreal, Canada)

Modelling the rhythm of life:

More than 50 years of iterationof modelling and physiology

From Hodgkin & Huxley…

Alan Lloyd

Hodgkin(1914-1998)

Andrew Fielding

Huxley(1917-2012)

… to Denis Noble …

Denis Noble(1936-present)

… to current human models

{O’Hara et al. PLOS Comput Biol. 2011}

Sodium channel schematic

Sodium channel equation

Based on experimental data from>150 human hearts.

Still largely based on Hodgkin-Huxleymodel and its formulation of voltage-gated ion channel behaviour.

Towards regulatory and industry acceptance

U.S. Food and Drug Administration:

Comprehensive In Vitro Proarrhythmia Assay (CiPA) Initiative (2013):“Rechannelling the Current Cardiac Risk Paradigm”

In silico assay to evaluate nonclinical data and assess risk.

Avicenna Roadmap:

“In silico clinical trials: How computer simulations will transform thebiomedical industry” (http://avicenna-isct.org/roadmap/)

Analysis of expert opinion surveys and syndicate discussions:

• Current modelling capabilities are not holding up acceptance.• Need of convincing evidence on its optimal use in pharmaceutical,

regulatory and clinical sectors.

Mathematical modelling inSafety Pharmacology

We are all different

Human atrialmyocytes(n=35)

(n=18)

Courtesy: Xing Liu & Barbara Casadei Britton et al., submitted Courtesy: Aurore Lyon

Subject 1

Subject 22

60 80 140

20 60 80 140

Time (ms)

0

- 2

0

1

QR

Sle

ad

V5

(mV

)Q

RS

lea

dV

5(m

V)

20

Human ventricularmyocytes (n = 39 hearts)

Time (ms)

40

-80

Mem

bra

ne

po

ten

tial

(mV

)

0 500

Differences in electrophysiological function between individuals are present atmultiple scales in the heart.

Ionic currents Cellular action potential Whole heart (ECG)

Is the “average cell” enough?

n = 62 experimental traces

Original O’Hara-Rudy AP model

Population of Models

{Britton, Bueno-Orovio, Virág, Varró, Rodriguez. In submission}

The Population of Models approach

Baseline model (average cell behaviour)+ variability (model parameters)

Populations of human in silico cells(same biology, different ionic profiles)

Experimentalcalibration

{Britton, Bueno-Orovio, Van Ammel, Lu, Towart, Gallacher, Rodriguez. PNAS, 2013}

(Winning paper,2014 NC3Rs 3Rs Prize)

Evaluation study

In silico prediction of 55 different compounds:

o Drug inhibitory profiles: Kramer et al. Sci Rep 2013;3:2100.

o Mixture of drug types: anti-arrhythmics, cancer therapy, antibiotics,antihistamines, antipsychotics.

o 8 withdrawn from market.

In vivo risk assessment:

o CredibleMeds (https://crediblemeds.org/).

o Risk classification: 32 TdP risk / 23 no TdP risk.

Methodology:

o Population of 1,213 human ventricular models.

o Drug dosage: from 1x to 100x EFTPCmax.

o Simple pore-block drug model: IC50 and Hill coefficient.

{Passini, Britton, et al. In submission.}

Evaluation study: Summary

{Passini, Britton, et al. In submission.}

Officially Sensitive

Virtual Assay software

Human

Allows use ofmethodologyin industry withoutprogramming andmodelling expertise.

In silico prediction of variability in drug response:

Infrastructure for Impact Award

Academia Industry Clinical Regulators

Non-diseased models for cardiotoxicity

Diseased models for cardiotoxicity

Transparent comparison of technologies

In silico human cardiotoxicity

Infrastructure for Impact Award

Non-diseased models for cardiotoxicity

Diseased models for cardiotoxicity

Transparent comparison of technologies

In silico human cardiotoxicity

Mathematical modelling in biology

Complex nature of biology:• Models as tools to augment experimental/clinical findings.

Multiscale modelling and simulation allows:• Investigation of secluded and concurrent factors in disease.• Qualitative and quantitative predictions.• Identification of physiological mechanisms.• Prediction of potential therapeutic targets.• Guidelines to design/refine new experiments.

A focus on human, rather than animal:• Increased relevance for clinical translation.• 3Rs (Reduction, Refinement, and Replacement) of animal experimentation.

Development of new economical sectors:• In silico clinical trials for drug screening.

Thank You!