IC06 Gastrointestinal System PK Concepts for Distribution, AY2024/25 PDF

PR2152 Gastrointestinal System IC 06 PK concepts for Distribution I AY2024/25 Sem 1 Chng Hui Ting, PhD E-mail: [email protected] 1 Overview of Distribution lectures Part 1...

PR2152 Gastrointestinal System IC 06 PK concepts for Distribution I AY2024/25 Sem 1 Chng Hui Ting, PhD E-mail: [email protected] 1 Overview of Distribution lectures Part 1 Part 2 1) What factors affect the extent of 1) What PK parameters can I derive from the distribution of drugs? PK profile of a drug following two- 2) It appears that not all drugs follow the compartment model, following IV bolus assumption that they distribute dose? instantaneously to all tissues upon 2) What factors affect the rate of distribution administration. For these drugs, how do of drugs? we describe their disposition? What PK processes are happening? 3) What is the clinical significance of learning about drugs following multi- compartmental models? 2 Distribution Part 1 LEARNING OUTCOMES At the end of this part, students should be able to: Explain the factors that affect the extent of distribution of drugs using protein binding equation and tissue distribution models Relate the fundamental concepts of the extent of drug distribution to its clinical relevance Describe the PK processes and different apparent volume of distribution associated with drugs with a disposition following two-compartment model 3 RECAP from PR1153 4 RECAP from PR1153 5 RECAP from PR1153 Clinical application of V: to glean distribution characteristics of a drug Protein drugs have V close to plasma volume due to their large molecular size (unable to cross cell membrane to be distributed to tissues) Basic compounds tend to have large V than acids Diagonal lines Protein drugs Why do basic (half-lives) compounds tend to Basic drugs have large V? Acidic drugs Digoxin is neutral 3L (plasma volume) Amphotericin B is both an acid and a base © Copyright National University of Singapore. All Rights Reserved. 6 RECAP from PR1153 Plasma & tissue protein binding Concept: Unbound fraction Protein- Free/unbound Drug bound bound drug drug to RBC Blood/Plasma 𝑓𝑓𝑢𝑢 = 𝐶𝐶𝑢𝑢 𝑓𝑓𝑢𝑢 = 𝐶𝐶 𝐶𝐶𝑢𝑢 𝑓𝑓𝑢𝑢𝑏𝑏 = 𝑓𝑓𝑢𝑢𝑢𝑢 = 𝐶𝐶𝑏𝑏 Tissues (muscles, fats, liver, brain etc) 𝐶𝐶𝑢𝑢𝑢𝑢 𝑓𝑓𝑢𝑢𝑢𝑢 = 𝑓𝑓𝑢𝑢𝑢𝑢 = 𝐶𝐶𝑇𝑇 © Copyright National University of Singapore. All Rights Reserved. 7 RECAP from PR1153 Plasma & tissue protein binding Concept: Equilibrium Protein- Free/unbound Drug bound bound drug drug to RBC There are various equilibria to consider here: 1)Bound-unbound drug in plasma/ blood 2)Bound-unbound drug in tissue 3)Equilibrium between blood and tissue compartments What are examples of plasma proteins that bind to drugs? © Copyright National University of Singapore. All Rights Reserved. 8 Model describing distribution of drugs Factors affecting plasma protein binding i.e. fu Factors affecting tissue protein binding Factors affecting volume of tissue WHAT FACTORS AFFECT THE EXTENT OF DISTRIBUTION OF DRUGS? 9 RECAP from PR1153 Drug-tissue protein binding characteristics Acidic (anionic) drugs Basic (cationic) drugs Tend to have smaller V (< 1 Typically have larger V (> 1 L/kg) despite L/kg) due to their high affinity comparable affinity for plasma proteins for plasma albumin and low because of extensive tissue protein binding binding affinity for tissue and other sequestration mechanisms proteins Basic drugs bind to tissue acidic phospholipids Drug example: Tolbutamide Drug example: Propranolol V = 0.15 L/kg V = 4 L/kg fu = 5-10% fu = 5-10% 𝐶𝐶𝑇𝑇 What is fu? 𝐶𝐶 10 Tissue-to-plasma equilibrium ratio After distribution equilibrium has been established, 𝐶𝐶𝑇𝑇 15 Ka1 Plasma 𝐾𝐾𝑃𝑃 = 𝐾𝐾𝑃𝑃 = 8 𝐶𝐶 = 1.88 KP = tissue-to-plasma equilibrium distribution ratio varies from one tissue to another (as seen from previous KP example of metoprolol) (muscles, fats, liver, brain etc) Tissues Distribution equilibrium is achieved Ka4 when, Cu = CuT i.e. net flux of free Ka3 Ka2 drug movement is zero 11 Model of tissue distribution Tissue 1 Plasma Tissue 2 Amount VT1. KP1. C VP.C VT2. KP2. C of drug Volume VT1 VP VT2 At distribution equilibrium, Amount in body = Amount in plasma + Amount outside plasma 𝐶𝐶𝑇𝑇 𝑉𝑉 𝐶𝐶 = 𝑉𝑉𝑃𝑃 𝐶𝐶 + 𝑉𝑉𝑇𝑇𝑇 𝐶𝐶𝑇𝑇𝑇 + 𝑉𝑉𝑇𝑇𝑇 𝐶𝐶𝑇𝑇𝑇 ….. Since 𝐾𝐾𝑃𝑃 = 𝐶𝐶 𝑉𝑉 𝐶𝐶 = 𝑉𝑉𝑃𝑃 𝐶𝐶 + 𝑉𝑉𝑇𝑇𝑇 𝐾𝐾𝑃𝑃𝑃 𝐶𝐶 + 𝑉𝑉𝑇𝑇𝑇 𝐾𝐾𝑃𝑃𝑃 𝐶𝐶….. We combine all volumes outside plasma to be VT and take CT to be the average total drug concentration throughout that volume, 𝑉𝑉 𝐶𝐶 = 𝑉𝑉𝑃𝑃 𝐶𝐶 + 𝑉𝑉𝑇𝑇 𝐶𝐶𝑇𝑇 -------- (1) 12 Model of tissue distribution At distribution equilibrium, Amount in body = Amount in plasma + Amount outside plasma 𝑉𝑉 𝐶𝐶 = 𝑉𝑉𝑃𝑃 𝐶𝐶 + 𝑉𝑉𝑇𝑇 𝐶𝐶𝑇𝑇 -------- (1) Dividing equation (1) by C, 𝐶𝐶𝑇𝑇 -------- (2) 𝑉𝑉 = 𝑉𝑉𝑃𝑃 + 𝑉𝑉𝑇𝑇 𝐶𝐶 𝐶𝐶𝑢𝑢 𝐶𝐶𝑢𝑢𝑢𝑢 𝐶𝐶𝑢𝑢 because at distribution Since, 𝑓𝑓𝑢𝑢 = and 𝑓𝑓𝑢𝑢𝑢𝑢 = = equilibrium, Cu = CuT 𝐶𝐶 𝐶𝐶𝑇𝑇 𝐶𝐶𝑇𝑇 𝐶𝐶𝑇𝑇 𝑓𝑓𝑢𝑢 -------- (3) = 𝐶𝐶 𝑓𝑓𝑢𝑢𝑢𝑢 Substitute (3) into (2), What’s the meaning of this 𝑓𝑓𝑢𝑢 -------- (4) equation? How is it useful? 𝑉𝑉 = 𝑉𝑉𝑃𝑃 + 𝑉𝑉𝑇𝑇 𝑓𝑓𝑢𝑢𝑢𝑢 13 Model of tissue distribution What factors affect fu, fuT and VT? What is its impact on V? Gibaldi and McNamara model Physiologic volumes – can be estimated Can be determined i.e. 3 L plasma, 39 L tissue water experimentally in the lab 𝑉𝑉 = 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 (𝑚𝑚𝑚𝑚) = 𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿𝐿 Perform equilibrium dialysis 𝐶𝐶0 (𝑚𝑚𝑚𝑚/𝐿𝐿) Can be determined 𝑓𝑓𝑢𝑢 from experiment 𝑉𝑉 = 𝑉𝑉𝑃𝑃 + 𝑉𝑉𝑇𝑇 𝑓𝑓𝑢𝑢𝑢𝑢 Looking at this equation and the earlier 𝑉𝑉 = 𝑉𝑉𝑃𝑃 + 𝑉𝑉𝑇𝑇 𝐾𝐾𝑃𝑃 , 𝑓𝑓 It is seen that 𝐾𝐾𝑃𝑃 ≈ 𝑢𝑢  it is a measure of the relative binding of a drug between 𝑓𝑓𝑢𝑢𝑢𝑢 plasma and tissue  this is the term that gives the “apparentness” of V Aids in interpreting data on V i.e. we are unable to predict if a drug will likely have a high or low V just looking at fu (plasma protein binding) The equation also enables estimation of fuT which is the average value across all tissues into which drug distributes 14 Plasma protein binding: free drug fraction (fu) Protein Drug Drug-protein complex Ka 𝐶𝐶𝑏𝑏𝑏𝑏 𝐾𝐾𝑎𝑎 = + Kd 𝐶𝐶𝑢𝑢 𝑃𝑃 1 𝑓𝑓𝑢𝑢 = (1 + 𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ) 𝑃𝑃 Affinity specific between a Concentration of 𝑓𝑓𝑢𝑢𝑢𝑢 = particular drug and protein unoccupied protein 𝑃𝑃𝑇𝑇 Ka is association constant Cu is concentration of unbound drug Cbd is the concentration of bound drug What can affect Ka or PT? P is concentration of unoccupied protein PT is concentration of total protein fup is the fraction of the total of binding sites unoccupied 15 Factors affecting free drug fraction (fu) 1 ①Alterations to PT due to disease: 𝑓𝑓𝑢𝑢 = (1 + 𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ) Decreased hepatic biosynthesis of albumin in uremia and cirrhosis Induction of α1-AGP in uremia, inflammatory diseases, trauma & cancer Propranolol (V: 4L/kg, %protein binding: ~90%) Data from 78 patients with various diseases and healthy volunteers (diamond shape) 16 Factors affecting free drug fraction (fu) 1 ②Alterations to P (concentration of unoccupied protein) : 𝑓𝑓𝑢𝑢 = (1 + 𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ) Drug-drug interaction (refer e-learning on DDI involving protein 𝑃𝑃 binding) 𝑓𝑓𝑢𝑢𝑢𝑢 = 𝑃𝑃𝑇𝑇 ③Alterations to Ka : Genetic variants of albumin & α1-AGP Disease-induced modification in α1-AGP carbohydrate moieties Big idea: fu is relatively stable for a particular PT level Therefore, C is a good representation of Cu If there’s any changes, it could be due to genes, disease or DDI affecting Ka, P or PT If patient has a disease that causes a change in PT (total protein), can we determine the new fu’ ? 17 Calculating changes in fu 1 Question: 𝑓𝑓𝑢𝑢 = Given that fu ibuprofen = 0.005 in normal adults. (1 + 𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ) The albumin concentration in a patient with alcoholic cirrhosis decreased from 43 g/L to 28 g/L. Considering drugs with low fu (highly protein Determine the new fu’ for this patient. bound), we can approximate the equation to: 1 𝑃𝑃𝑇𝑇 𝑓𝑓𝑢𝑢 = 𝑓𝑓𝑢𝑢′ = × 𝑓𝑓𝑢𝑢 (𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ) (𝑃𝑃𝑇𝑇 ′) 43 When PT is altered to PT’: = × 0.005 (28) 1 = 0.0077 (54% increase!!) 𝑁𝑁𝑁𝑁𝑁𝑁 𝑓𝑓𝑢𝑢′ = (𝐾𝐾𝑎𝑎 𝑓𝑓𝑢𝑢𝑢𝑢 𝑃𝑃𝑇𝑇 ′) If fu is altered, does V necessarily changed?? 𝑃𝑃𝑇𝑇 𝑁𝑁𝑁𝑁𝑁𝑁 𝑓𝑓𝑢𝑢′ = × 𝑓𝑓𝑢𝑢 (𝑃𝑃𝑇𝑇 ′) eL03 Slide 8 Impact of change in fu on V  fu  V = VP + VT ⋅    fuT  Propranolol (V: 4L/kg, %protein binding: ~90%) For drugs with large V (>1L/kg) Changes in fu result in proportionate change in V For drugs with small V (~0.7) Changes in fu result in minimal change (Low EH) in CL For drugs with low EH ( 42L (Total Body Water in 70kg persion) What is the clinical relevance of learning about multi-compartmental models? Wall, et al. (1983). Metabolism, disposition, and kinetics of delta-9-tetrahydrocannabinol in men and women. Hunt, C. A., & Jones, R. T. (1980). Tolerance and disposition of tetrahydrocannabinol in man. Sempio, et al. (2020). Population pharmacokinetic modeling of plasma Δ9-tetrahydrocannabinol and an active and inactive metabolite following controlled smoked cannabis administration. Kelly, P., & Jones, R. T. (1992). Metabolism of tetrahydrocannabinol in frequent and infrequent marijuana users. Clinical relevance of concepts on multi-compartmental model In clinical practice e.g. therapeutic drug monitoring (TDM), we try to minimize the need to draw too many samples (unlike in a full PK study where blood samples are drawn at many time-points) Time of sampling during TDM is critical for drugs following two-compartment model (e.g. aminoglycosides, digoxin, lithium)  incorrect timing may lead to erroneous determination of elimination half-life  improper dose adjustments 38 Clinical relevance of concepts on multi-compartmental model Big idea: Many drugs exhibit distributional, multi-compartment disposition Mathematical equations can be complex, but important in the research and drug discovery context for characterizing PK of drugs accurately In clinical context, it is common to see 1-compartment model being used if it can provide reasonable prediction of drug concentrations or calculations of PK parameters Important clinical relevance: Onset of action for some drugs may be slow if the target is in the peripheral compartment To choose correct sampling time to determine elimination half-life accurately 39 Distribution Part 1 sub-topic summary 1) What factors affect the extent of 2) It appears that not all drugs follow the distribution of drugs? assumption that they distribute – Model describing distribution of drugs instantaneously to all tissues upon – Factors affecting plasma protein administration. For these drugs, how do we binding i.e. fu describe their disposition? What PK – Factors affecting tissue protein binding processes are happening? – Factors affecting volume of tissue – Two-compartment model – PK processes happening – Different apparent volume of distribution – Clinical relevance 40