Challenges in Infectious Diseases Lessons from tuberculosis Gerry - - PowerPoint PPT Presentation

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Challenges in Infectious Diseases Lessons from tuberculosis Gerry - - PowerPoint PPT Presentation

Challenges in Infectious Diseases Lessons from tuberculosis Gerry Davies Senior Lecturer in Infection Pharmacology Institutes of Global Health and Translational Medicine Consortium for Pharmacokinetics & Pharmacodynamics of Infectious


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Challenges in Infectious Diseases

Lessons from tuberculosis

Gerry Davies

Senior Lecturer in Infection Pharmacology Institutes of Global Health and Translational Medicine

Consortium for Pharmacokinetics & Pharmacodynamics of Infectious Agents

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 More than one biological system/entity  Combination therapy routine  Complex patterns of pharmacodynamic response  Persistence and resistance  Microbiological versus clinical response  Important events below LOD  Empirical versus mechanistic approaches

What's so different about infectious diseases ?

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2 billion latent infections

26% of avoidable adult deaths in developing world 2 million deaths /yr

8-10 million new cases/yr

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Short Course treatment for TB

SHR HR SHRZ/TH SHRZ/SHZ

Relapse 6 months 2 months

10 20 30 40 Percent Positive

SHRZ/HRZ SHRZ/HR SHRZ/HZ SHRZ/H HRZ/H

Relapse 6 months 2 months

10 20 30 40 Percent Positive

N=953 ~240 per arm N=696 ~130 per arm

THE LANCET, NOVEMBER 9, 1974 CONTROLLED CLINICAL TRIAL OF FOUR SHORT- COURSE (6-MONTH) REGIMENS OF CHEMOTHERAPY FOR TREATMENT OF PUMONARY TUBERCULOSIS

SECOND EAST AFRICAN / BRITISH MEDICAL RESEARCH COUNCIL STUDY

THE LANCET, AUGUST 12, 1978 CONTROLLED CLINICAL TRIAL OF FIVE SHORT-COURSE (4-MONTH) CHEMOTHERAPY REGIMENS IN PULMONARY TUBERCULOSIS

First Report of 4th Study

EAST AFRICAN AND BRITISH MEDICAL RESEARCH

COUNCILS

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TB pandemic 2010

80% in 22 high burden countries 30% in India & China

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New anti-tuberculosis drugs

Rifabutin Rifapentine Levo/ofloxacin Moxifloxacin Gatifloxacin PA-824 OPC-67683 TMC-207

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15 BMRC trials 6974 participants 37 treatment comparisons

Bacteriological biomarkers are useful surrogate endpoints

Phillips PJ et al IUATLD Cape Town 2007

Phillips P and Fielding K 2008 IUATLD Conference Paris

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  • 0.2
  • 0.1

0.1 0.2 0.3 0.4 0.5 0.6 1 10 100 1000 10000

Log Dose (mg) EBA

0-2 (Log 10 CFU/ml/day) H R Rb Rp Cp S

Early Bactericidal Activity

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Bacillary elimination is biphasic

Nairobi SHRZ N=46 Durban HRZE N=50 Bangkok HRZE N=44 Davies G Tuberculosis (Edinb). 2010 90(3):171-6

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Modelling Phase II trials

Predictions from unadjusted model

Rustomjee R et al . Int J Tuberc Lung Dis. (2008) 12(2):128-38

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Limit of detection

N=159

NONMEM M3 Method WinBUGS I() Method

Davies Gordon Conference on TB drug development 2011

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Power advantages of NLME

Randomize d treatment allocation in blocks of 10 Generate profiles of bacillary load from day 7 -56 Generate individual day 7 intercept and slope from random effect distributions Censor at limits of detection Generate datasets for each form of analysis Store effect sizes, p-values, culture conversion rates N >

  • No. of

simulations ? Compute power and plot diagnostics Compute summary statistics and perform analyses

N+1

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N=31 N=31

p=0.010 p=0.635

Detection of PK-PD relationships

Isoniazid Rifampicin

Abstract OI-106 CROI 2008

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Patterns of PD response

Bedaquiline (TMC-207) Delaminid (OPC-67683)

Diacon AH 2011 IJTLD 15(7):949–954 Rustomjee R 2008 AA&C 52(8):2831-5

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Fast Slow

Speed of bacterial growth

A CONTINUOUS GROWTH

D DORMANT B ACID INHIBITION C SPURTS OF METABOLISM

H (R, S) Z R

The Subpopulations hypothesis

Mitchison 1978 Canetti 1969

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Persister phenotype in sputum

Garton NJ PLoS Med 2008 5(4):e75 Schoolnik Keystone 2009

334 genes down- regulated in both NRP2 and sputum 182 genes up- regulated in both NRP2 and sputum

icl,hspX,whiB6 fadD & E families, other members

  • f dosR regulon

rpl, rps, atp, nuo, inhA, fas,whiB1, sigH, sigD

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Semi-mechanistic PD model

Davies GR Tuberculosis (Edinb). 2010 90(3):171-6

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Disease modelling in TB

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Summary

 A PK-PD approach promises more rational clinical development of new combination therapies for tuberculosis  Efficient proof-of-concept, screening of combinations and dose-finding may be possible using model-based designs  Mechanistic modelling of the underlying mechanisms of sterilization may be the only way to correctly interpret the results of future early phase clinical trials

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Acknowledgements

Mahidol-Wellcome-Oxford SEA Unit

Nick White Kasia Stepniewska Wirongrong Cheirakul

St George’s / InterTB

Dennis Mitchison Amina JIndani David Coleman

Training fellowship GR067910MA PKPDia Programme grant

  • Dept. of Pharmacology,

University of Liverpool

Saye Khoo Dave Back Andrew Owen

CAPKR, University of Manchester

Leon Aarons

South African Medical Research Council, Durban

Roxana Rustomjee Jonathan Levin Jenny Allen Alex Pym

Bamrasnaradura Infectious Diseases Institute Nartpratou Saguenwong

Boonchuay Eompokalap

Siriraj Hospital, Faculty

  • f Medicine

Nitipatana Cheirakul Angkana Chaiprasert

Oflotub Consortium

Christian Lienhardt

Tom Kanyok John Horton

Harvard University & Socios en Salud

Carol Mitnick

CDC TB trials consortium

Chad Heilig Andy Vernon

Liverpool School of Tropical Medicine

Steve Ward Bertie Squire Andy Ramsay