Clinical Pharmacology of Antimicrobials in Children

Transcription

1 Clinical Pharmacology of Antimicrobials in Children Joe Standing MRC Methodology Fellow & Antimicrobial Pharmacist UCL Institute of Child Health Great Ormond Street Hospital for Children March / 43

2 2 / 43

3 What you should get (AKA Learning Objectives): Know the pharmacology of some common antimicrobials Understand what pharmacokinetics means, and how it links with clinical effect (pharmacodynamics) Recognise how pharmacokinetics scales in children 3 / 43

4 Overview Antimicrobial pharmacology Introduction to pharmacokinetics Linking pharmacokinetics to clinical effect Scaling pharmacokinetics in children Case studies 4 / 43

5 Antimicrobial pharmacology: β - lactams Irreversible binding to DD-transpeptidase Inhibits cross-linking of cell wall peptidoglycan Requires near saturation for lysis Many organisms produce β - lactamase e.g. Penicillins, cephalosporinns, carbapenems (>50% of antimicrobials used are β - lactams) 5 / 43

6 Antimicrobial pharmacology: Other cell-wall inhibitors Glycopeptides: e.g. vancomycin, teicoplanin Inhibits peptidoglycan chain elongation Mainly Gram positive activity Antifungal agents: Azoles inhibit ergosterol synthesis Echinocandins inhibit glucan synthesis Polyene agents, e.g. amphotericin, bind to ergosterol creating transmembrane pore 6 / 43

7 Antimicrobial pharmacology: Nucleic acid synthesis inhibitors Inhibition of precursors: e.g. sulphonamides, trimethoprim Inhibition of folate synthesis Inhibition of replication: e.g. quinolones Inhibits ligase part of topoisomerase II meaning DNA is not re-joined Direct DNA damage: e.g. metronidazole Following non-enzymatic reduction in anaerobic environment, various metabolites and cause DNA cross-linkage/direct damage Transcription: e.g. rifamycins Inhibition of prokaryotic RNA polymerase 7 / 43

8 Antimicrobial pharmacology: Protein synthesis inhibitors mrna translation: e.g. aminoglycosides, tetracyclines Bind to 30S ribosome subunit Inaccurately formed proteins, incorporate to cell wall, can lead to further antimicrobial penetration Protein formation: e.g. macrolides, chloramphenicol Bind to 50S ribosome subunit Peptidyl transferase inhibition 8 / 43

9 Antimicrobial pharmacology: antiretrovirals Reverse transcriptase inhibitors: Nucleoside or non-nucleoside Inhibit viral incorporation to host DNA Protease inhibitors: Cause production of defective virus Entry inhibitors: Block viral entry e.g. via CCR5 Integrase inhibitors: Inhibit viral incorporation to host DNA 9 / 43

10 Overview Antimicrobial pharmacology Introduction to pharmacokinetics Linking pharmacokinetics to clinical effect Scaling pharmacokinetics in children Case studies 10 / 43

11 Introduction to Pharmacokinetics: Absorption Bioavailability F [0, 1] F = Fa Fg Fh 11 / 43

12 Introduction to Pharmacokinetics: Distribution Important factors: flow, partition, protein/tissue binding 12 / 43

13 Introduction to Pharmacokinetics: Metabolism Major sites: LIVER, gi tract Minor sites: kidneys, lungs Enzymatic reactions: make things more water soluble Phase I: Cytochrome P450 (e.g. CYP3A4, CYP2D6) Phase II: Multiple (e.g. UGT) Well-stirred liver model: CL H = FQ CL int FQ + CL int. (1) 13 / 43

14 Introduction to Pharmacokinetics: Elimination 14 / 43

15 Introduction to Pharmacokinetics: Some data Descriptive analysis: AUC, Cmax, tmax, elimination half-life How about a model? 15 / 43

16 Introduction to Pharmacokinetics: One-compartment model C(t) = Dose k a V (k a k) (e k t e ka t ), k = CL V. Note: models such as this describe/predict circulating concentrations. Physiologically-bases systems pharmacology models can help predict tissue concentrations. (2) 16 / 43

17 Overview Antimicrobial pharmacology Introduction to pharmacokinetics Linking pharmacokinetics to clinical effect Scaling pharmacokinetics in children Case studies 17 / 43

18 Linking Pharmacokinetics and Pharmacodynamics 18 / 43

19 Pharmacological Response Law of mass action: Drug (D) combining with Receptor (R) [D] + [R] [DR]. (3) Quantities of interest: k 1, rate of association k 2, rate of dissociation K D, dissociation constant K D = k 2 k 1 = [D] [R]. (4) [DR] 19 / 43

20 Concentration-Effect: Hill curve Effect = E max C γ EC50 γ + C γ. (5) 20 / 43

21 Pharmacokinetic compared with pharmacodynamic time-course 21 / 43

22 Antimicrobial PKPD: Simplest case McKinnon 2004: 22 / 43

23 Antimicrobial PKPD: Static in vitro experiments Elucidating PKPD in vitro e.g. Drusano 2004: 23 / 43

24 Linking PK and PD Quite often: PD time course PK time course. Hysteresis: 24 / 43

25 Antimicrobial PKPD: Dynamic in vitro experiments e.g. Nielsen 2011 Antibacterial dosing usually based on worst-case scenario (no immune component) Scaling to children involves accounting for pharmacokinetic ontogeny 25 / 43

26 Antimicrobial PKPD: e.g. HIV disease progression After starting antiretroviral treatment, CD4 lymphocytes recover, and circulating virus is suppressed: 26 / 43

27 Basic model of HIV 27 / 43

28 Overview Antimicrobial pharmacology Introduction to pharmacokinetics Linking pharmacokinetics to clinical effect Scaling pharmacokinetics in children Case studies 28 / 43

29 Children are not small adults Pharmacokinetic differences: Absorption: Gastric ph, motility, bile salts, flora, milk feeds Distribution: body water, body fat, plasma proteins Metabolism: liver size, metabolising enzymes Elimination: liver size, metabolising enzymes 29 / 43

30 Children are small adults; neonates and infants are immature children Maturation is continuous By 2 years of age, most processes involved with drug handling are mature Differences in children above 2 years and adults mainly due to size How to scale for size? Volume tends to be linear Clearance and metabolic processes follow allometric relationship: Y = a W b. (6) where: Y = biological characteristic; W = weight; a and b are derived coefficients. 30 / 43

31 Kleiber 1947: Drug Clearance: Allometric Scaling 31 / 43

32 Drug Clearance: Allometric Scaling Burger 2007: 32 / 43

33 Drug Clearance: Allometric Scaling Anderson 2007: 33 / 43

34 Overview Antimicrobial pharmacology Introduction to pharmacokinetics Linking pharmacokinetics to clinical effect Scaling pharmacokinetics in children Case studies 34 / 43

35 Antimicrobial PKPD: Dynamic in vitro experiments Gentamicin: narrow therapeutic index aminoglycoside Dosing in neonates poorly defined Nielsen et al: Collected and modelled PK data in neonates Performed static and dynamic in vitro experiments versus E. coli and fitted model including adaptive resistance Combined the in vivo PK modelling with the in vitro PD modelling to investigate different dosing regimens 35 / 43

36 Antimicrobial PKPD: Dynamic in vitro experiments 36 / 43

37 Case study 2: HIV Personalised medicine HIV patients often experience medication side-effects Minimising dosing whilst still ensuring viral suppression is attractive Prague 2012, activated cells model: 37 / 43

38 Prague / 43

39 Case study 3: drug-induced neutropenia Lots of drugs deplete neutrophils (side effect) Quantifying, predicting and avoiding neutropenia is important: In 2009, 3 people died of neutropenic sepsis for every 1000 cancer diagnoses. (Prevention and management of neutropenic sepsis in cancer patients: NICE 2012) 39 / 43

40 Case study 3: Neutropenia time course Some analysts have focussed on time to nadir or depth of nadir; is this ideal? 40 / 43

41 Case study 3: Friberg model In 2002 Friberg described neutrophil maturation with a system of ODEs dp dt = k prol P (1 E drug ) (C(0)/C(t)) γ k tr P dt 1 = k tr P k tr T 1 dt dt 2 = k tr T 1 k tr T 2 dt dt 3 = k tr T 2 k tr T 3 dt dc dt = k tr T 3 k tr C. (7) 41 / 43

42 Case study 3: Friberg 2002 Unlike empirical models linking depth of/time to nadir with dose, the mechanistic approach predicts the full time-course Because underlying system is captured, the model can be used for extrapolations (e.g. Soto 2011) and dose adjustments (e.g. Wallin 2009) 42 / 43

43 What you should get (AKA Learning Objectives): Know the pharmacology of some common antimicrobials Understand what pharmacokinetics means, and how it links with clinical effect (pharmacodynamics) Recognise how pharmacokinetics scales in children 43 / 43