1. Should we change the recommendations related to antibiotic drug dosage/drug duration? Workshop on Economic Epidemiology Makerere University August, 2009 Patricia Geli Rolfhamre

2. Acknowledgements Ramanan Laxminarayan, Resources for the Future David L. Smith, Resources for the Future Simon Levin, Princeton University Michael Dunne, Advisory committee “Extending the Cure”

3. Agenda How are antibiotic guidelines developed? Are we basing all dosing regimens on TB experience? How can the guidelines be improved? Consequences v. benefit of different guidelines Conclusions and take home message

4. A drug to cure bacterial infections Second most widespread drug after analgesics: Majority of the population will take antibiotics at some time in their lives

5. Development of drug dose/duration guidelines 1930s 1940s 1950s 1960s 1970s 1980s 1990s 2000s Relationships between drug dose/duration and therapeutic efficacy – only beginning to be understood for many antibiotics Introduction of first antibiotic for clinical use

6. Development of drug dose/duration guidelines Ex: Aminoglycosides 1930s 1940s 1950s 1960s 1970s 1980s 1990s 2000s Relationships between drug dose/duration and therapeutic efficacy – only beginning to be understood for many antibiotics Is leading to dramatic changes in drug dose/duration recommendations Now: Single large daily dose Then: Three smaller doses per day

7. Historically designed to achieve: - maximal treatment efficacy - minimal toxicity Development of drug dose/duration guidelines

8. Historically designed to achieve: - maximal treatment efficacy - minimal toxicity BUT... Resistance not considered! Development of drug dose/duration guidelines

9. Resistance comes fast... J. Davies, 1997

10. ...is still growing Source: NNIS DATA, Clinics Chest Med. 20:303-315 ICU Patients Non-ICU Patients

11. “Selective pressure comes from a combination of overuse in many parts of the world, particularly for minor infections, misuse due to lack of access to appropriate treatment and underuse due to lack of financial support to complete treatment courses” The Paradox Cited from: World Health Organization (2009), Community-Based Surveillance of Antimicrobial Use and Resistance in Resource-Constrained Settings

12. From individuals to public health: DOTS for TB Treatment and prevention of resistance in individuals = key public health measure

13. This works for TB – but is it sound for other infections?

14. When and why do we treat? 50% of all consumption for respiratory tract infections (RTI) Most common symptoms: otitis media sore throats sinusitis,...

15. Duration v. benefit of treatment Many RTI symptoms are likely to be caused by viruses, i.e. no benefit of antibiotic treatment Even if bacterial, recent clinical evidence suggests that shorter drug durations can be equally effective as longer ones For acute otitis media (middle ear infection), the second most common infection after the common cold, 3 days has been shown to be as effective as 10 days

16. “Normal” flora 10 14 -10 15 bacteria (or 1-2 kg) totally in the human body S. aureus S. pneumoniae H. influenzae N. meningitidis E. coli, Klebsiella Enterobacter Enterococcus faecium

17. Treatment exerts selection on “innocent bystanders” Most of the harm done by use of a drug may be on species OTHER than the target of treatment Most of the exposure of a given species to a given drug may be due to treatment of OTHER infections Normal flora: Consequences

18. Resistance is contagious! It will continue to spread even after infection has been cleared Normal flora: Consequences

19. How can we investigate this further?

20. Traditional pharmacokinetic/ pharmacodynamic models Pharmacokinetics: what the body does to the drug Pharmacodynamics: what the drug does to the body Our knowledge comes mostly from experimental trials Immune responses NOT considered!

21. Growth R R Time Antibiotic concentration # Bacteria Pharmacokinetics/ Pharmacodynamics

22. Growth R Growth S Selective Window (SW) S R Time in SW Antibiotic concentration # Bacteria Selection of R Emergence and selection of resistance

23. S R Sensitive population Resistant population Traditional pharmacokinetic/ pharmacodynamic models

24. SR Sensitive population Resistant population Incorporating the immune response S I Sensitive population Immune response

25. Possible pathogen dynamics Unregulated bacterial dynamics: Commensal bacteria that uses body as a habitat Regulated bacterial dynamics: Bacteria and the immune response settles an equilibrium Self-limiting dynamics: Bacterial populations are reduced below a cut-off value (<1) and infection is successfully limited

26. Unregulated bacterial dynamics: the TB example Selective Window (SW) Time Time symptoms Time Resistance selection

27. Regulated bacterial dynamics: the normal flora example Selective Window (SW) Time Time symptoms Time Resistance selection

28. Regulated v. self-limiting dynamics Selective Window (SW) Time Time symptoms Time Resistance selection self-limiting dynamics Resistance selection regulated dynamics

29. Regulated v. self-limiting dynamics Selective Window (SW) Time Time symptoms Time Resistance selection self-limiting dynamics Resistance selection regulated dynamics Optimal dosing for treatment ≠ optimal to prevent resistance!

30. For unregulated and regulated bacterial dynamics, high concentrations for long durations are required to clear bacteria Time for clearance of TB does not exert selection in normal flora, because the two key agents in the three drug combination therapy for TB are not active against any other micro-organisms Consequences v. benefit of treatment for unregulated bacteria

31. Self-limiting infections are successfully cleared with “shorter” duration of therapy Shorter durations with therapy exert less selection of resistance in normal flora, but give slightly longer duration of symptoms Consequences v. benefit of treatment for self-limiting infections

32. Does the gain of treating the patient outweigh the risk related to resistance development? Some studies have reported a low, but increased incidence in number of complications from countries with lower prescribing for AOM Consequences v. benefit of treatment for self-limiting infections

33. One size does NOT fit all! We need to broaden the concept of selection of resistance when devising optimal dosing strategies – both for guidelines for future and existing antibiotics Conclusions

34. Alternative strategies to save our antibiotics for the next generation?

35. Webale! Thank you! Tack!