Pharmacokinetics Flashcards
Drug development process
Preclinical studies are used to establish suitability of a drug for clinical trials. They involve in vitro studies in cell and tissues and in vivo studies in animal models to characterise PK PD and toxicokinetics.
Phase 1 trials use healthy human volunteers to establish PK and PD over a dose range for safety pharmacology.
Phase 2 trials involve patient studies to establish the PK/PD relationship, efficacy and side effects.
Phase 3 patient studies are used to extend effectiveness and safety profiling prior to licencing. Different subpopulation responses can be investigated.
Phase 4 is post licencing confirmation of effectiveness and safety - could investigate DDIs or carry out bioequivalence studies with different formulations.
At the early stages of drug development, before new chemical entities (NCEs) are tested in man, DMPK analysis is used to assess safety/toxicity potentials of the drugs and for preclinical optimisation of doses in animal studies.
We need to ensure that the FIH dose is safe.
Preclinical DMPK studies
Microsomal stability and intrinsic clearance is assessed.
CYP450 inhibition studies can tell you which enzymes play the largest role in the metabolism of your drug - can inform possible DDI studies.
Permeability assays determine the absorption profile of your drug.
Reaction phenotyping studies determine the metabolising enzymes involved in the clearance of your drug. Enzymes that may be involved could be predicted from your drug structure.
Metabolite profiling is important for secondary pharmacology - the PK of these need to be investigated.
Species comparisons look at correlations between species and PK parameters like drug clearance. This helps us assess whether we can accurately predict PK in humans, and helps us identify a suitable animal model.
The final stage of preclinical PK involves animal testing.
LogP
LogP determines the ability of an uncharged compound to dissolve in lipids and water.
It is the logarithm to the base of 10 of the partition coefficient.
Partition coefficient = [organic] / [aqueous]
The higher the LogP the higher the lipophilicity.
The logP can give an indication of tissue absorption or permeation, which affects PK processes involving cell penetration (ADME).
Lipinski’s rule of 5 states that a logP <5 is ideal for oral formulations, but some literature suggest that this value should be changed to <3.
For compounds targeting the CNS, an ideal logP is around 2 and for GIT absorption, 1.35-1.8.
A high LogP value aids permeability across the plasma membrane. Very hydrophilic compounds may struggle to cross the plasma membrane.
However, if LogP is too high solubility is compromised so bioavailability will be impacted. Accumulation in fatty tissue is also highly likely, which is a toxicity signal.
Molecular weight
MW is the mass of a molecule in g/mol or Daltons.
Large molecules (> 500 g/mol) do not easily cross cell membranes. MW therefore gives an indication of tissue absorption or permeation, which would affect PK processes involving cell penetration.
Lipinski’s rule of 5 states that MW should be <500 Da for oral formulations.
The majority of clinically marketed drugs have a MW of less than 350.
Solubility
Solubility is defined by the maximum concentration of a substance that can be completely dissolved in an aqueous solvent at a certain temperature.
Poorly soluble compounds are prone to poor oral bioavailability.
This is dependent on the physiological pH of the environment and the pKa of the compound.
Solubility is important as the drug needs to dissolve in water in the GIT before it can be absorbed if it is administered orally.
A solubility of ≥ 1 mg/ml in aqueous solution at pH (1.2-7.4) is desired. You want your drug to remain soluble at a range of pH values as pH changes through the GIT. This is influenced by the pKa of the drug.
The Biopharmaceutics Classification System (BCS) uses solubility and permeability to determine absorption properties of a drug.
- Class I: high solubility and permeability
- Class II: low solubility, high permeability
- Class III: high solubility, low permeability
- Class IV: low solubility and permeability
The BCS is used to predict in vivo performance of a drug during drug development using in vitro measurement of solubility and permeability. Most drugs are in class II.
Poor solubility is an industry-wide problem. This adds increased risk, cost and time to development. Incomplete oral absorption may be expected.
We can get around poor solubility by formulating your drug as a salt
Intrinsic clearance
Intrinsic clearance is the intrinsic ability of a compound to be cleared without the influence of blood flow or plasma protein binding. It is a measure of the metabolic stability of the drug.
High intrinsic clearance indicates poor metabolic stability, rapid clearance from plasma and a short duration of action, which limits the effect of the drug.
Low intrinsic clearance indicates high metabolic stability. This can have advantages and disadvantages.
- Low clearance can mean prolonged duration of therapeutic action
- There can however be toxicity issues
- Rapid clearance is desirable for drugs such as anaesthetics to avoid prolonged unconsciousness and coma.
- Low clearance is desirable for drugs used for chronic conditions, as it decreases the number of doses required and so increases compliance.
The PK applications of this are:
- <10 ml/min/mg of protein – low clearance
- 10–50 ml/min/mg of protein – moderate clearance
- >50 ml/min/mg of protein – high clearance
The choice will depend on the purpose of the drug, but usually highly metabolically unstable compounds do not progress to preclinical trials.
Apparent permeability (Papp)
Apparent permeability (Papp) estimates the permeability across the interstitial epithelium. This can be derived from CaCo2 or MDCK cell lines or using PAMPA.
It is important for drug absorption from the gut, permeation into tissue and the influence of transporters.
The following CaCo2 Papp values indicate:
- < 10-6 cm-1: low in vivo absorption (0-20%)
- 10-6 - 10 X 10-6 cm-1: medium in vivo absorption (20-70%)
- > 10 X 10-6 cm-1: high in vivo absorption (70 - 100%)
The efflux ratio tells us if drug absorption is passive or if the drug is actively effluxed/uptaken.
Plasma protein binding
PPB tells us how well bound a compound is to plasma proteins.
Normally correlated to lipophilicity: lipophilic compounds tend to have higher PPB.
Drugs bound to PP are usually not available to cross cell membranes.
Highly protein bound drugs may have an increased t1/2
Assessing PPB of metabolites may be equally important and this may or may not be similar to the parent drug
The ideal PPB value may vary depending on the target, purpose of the drug, etc.
Compounds with PPB < 85% are usually are not an issue for PPB-mediated DDIs. Compounds with very high PPB can displace drugs with a lower affinity for plasma proteins, increasing the concentration of unbound drug. This may cause toxicity due to off-target binding.
Inhibition constant
The inhibition constant concerns enzyme and transporter inhibition.
The inhibition of main enzymes and transporters in the body needs to be quantified to avoid toxicity - compounds that act as inhibitors at sites other than the target site usually do not progress, especially CYP inhibitors
An inhibition constant of >10 µM usually suggest a low risk of inhibition
PK in preclinical animal studies
Pharmacokinetics are important preclinically as they define the expected active drug level in the target compartment, such as plasma.
When planning clinical studies we need to consider that exposure of the drug often correlates with drug action, so this needs to be quantified using parameters such as AUC, Cmax and t1/2, which depend on primary parameters like CL and Vd.
We need to quantify the compound’s PK profile in preclinical species, such as rats, dogs or macaques.
An effective dose is defined in the preclinical species. This must be translated to clinically relevant exposure in humans.
When considering the translatability of animal to human PK, we need to account for interspecies differences such as: target potency or affinity differences and metabolic differences.
Based on what you know about animal physiology and the properties of your drug, you can determine the most appropriate animal species to use for preclinical testing. For example, for drugs that you believe to be absorbed paracellularly, such as small hydrophilic drugs, dogs would not be an appropriate species to use for predicting absorption in humans, as they have larger spaces between their cells. The estimated rate of absorption would be higher than the actual rate in humans. The route of absorption can be predicted based on the size and lipophilicity of your drug.
Scientists are required to evaluate the effect of the drug on fertility, carcinogenicity, mutagenicity and teratogenicity.
Scaling up animal to human PK - Allometry
We can predict human in vivo clearance from data on in vivo clearance in other species.
If a change in e.g. weight across species shows a correlation with clearance, you can extrapolate this to humans. This is allometric scaling.
Allometry is the study of how the size of an organism affects its shape, anatomy, physiology, and behaviour.
It is based on the principle that clearance is related to body weight of the animal.
CL = a x W^m
- CL= clearance
- a = coefficient
- W = body weight
- m = allometric exponent (slope of log CL vs log weight)
Allometry is generally considered to give a good prediction, within 2-fold of the actual value. 3 or more species should be used to determine the relationship between weight and Cl of a particular drug.
Prediction of clearance is particularly poor for compounds with low clearance (metabolically stable). This is the most common category in modern drug development: error can be a factor of 10.
Most analysis has been retrospective.
Allometry has been extended to compounds primarily eliminated unchanged, involving transporters and is also used for biologics.
Analysing preclinical PK data
The preclinical PK data is analysed to provide a snapshot of PK parameters in preclinical species.
Non-compartmental PK analysis (NCA) is often used as this is simple, allows a rough estimate of key PK parameters and makes no assumption of compartments.
NCA involves basic calculations, all based around the area under the plasma concentration-time curve (AUC).
From the AUC, other PK parameters can be derived.
The AUC is derived from a plot of plasma concentration vs time.
AUMC is derived from a plot of the product of plasma concentration and time vs time.
Other parameters derived from NCA include the mean residence time (MRT), the total clearance (CL) and the volume of distribution (Vd/Vss).
Phase 1 PK - determining HED and FIH dose
Phase 1 clinical trials are first in human (FIH) studies.
The starting human equivalent dose (HED) has to be determined.
The no observable adverse effect level (NOAEL) is used for low risk compounds, usually small molecules as it is easier to determine what targets the molecule will hit in the body and therefore what side effects to look out for.
The minimal anticipated biological effective level (MABEL) is used for high risk compounds, such as those where there is little to no information about the target, the target is active on multiple transduction pathways or widely expressed, or for biologics.
The escalation dose scheme has to be chosen. This can be single ascending dose (SAD), or multiple ascending dose (MAD) where the lowest dose is given multiple times before it is increased.
Preclinical studies in animals will generate data about the effective and toxic doses.
However, animals are smaller than humans, so the volume of distribution is smaller.
Doses in animals are based on mg/kg, but we shouldn’t just convert the animal dose to humans based on body weight.
The body surface area (BSA) normalization method is used. BSA correlates well across several mammalian species.
We can therefore calculate the HED using:
HED = animal dose (mg/kg) x (animal Km / human Km)
Km = average body weight (kg) / BSA m2
To determine the HED, we can use the NOAEL determined in animal studies for the calculation.
However, we don’t just administer the HED for phase 1 clinical studies. A safety factor should be introduced for the FIH dose. The default safety factor is 10 (so divide HED by 10), but this may change depending on the drug. The safety factor may increase if severe toxicity is detected in animals or decrease if similar compounds have already been tested and the safety profile in humans is known.
Applying the safety factor gives us the maximum recommended starting dose (MRSD).
Dose data in more than one species will give better indication of NOAEL, so an MRSD calculated from NOAEL doses from multiple animal species is better.
Remember that Km is based on average weights of humans and animals, so it might need adjusting
TGN1412 and the MABEL approach
TGN1412 was a targeted treatment for rheumatic disease. It promotes T-cell proliferation, cytokine production and resistance to apoptosis.
It caused expansion of mAb T cell regulation in macaques at a dose of 50 mg/kg
It was given to humans in FIH study at 1/500th of the animal dose (based on NOAEL)
Caused a near fatal immunological response 1 hr post infusion, causing its withdrawal.
Subsequently, a proposal of the MABEL approach of FIH dose calculation was made. This is targeted towards high-risk compounds such as therapeutic proteins.
MABEL is based on all pharmacological activity profiles of the compound, including efficacy data and binding endpoints, not only the toxicological profile. Understanding signalling pathways involved can enable better predictions.
This is the dose which gives some pharmacological activity and is relatively safe.
There is no single method of calculating MABEL.
All available pharmacological data is used including:
- Binding endpoints (affinity, receptor occupancy)
- Functional endpoints (intracellular signalling, cytokine release etc)
- Pharmacokinetic modelling - a sort of virtual clinical trial could be carried out first
General considerations in calculating MABEL include:
- Mode of action - caution should be taken for fully novel compounds or targets. The relationship between dose and response should also be considered.
- Pharmacology of the target: tissue distribution in health and disease
- Relevance of animal models
- Patient population → aim to test sub-therapeutic doses for safety testing first before increasing to a dose expected to be efficacious
Analysing phase 1 PK data
Data from phase 1 trials is analysed using NCA, similarly to preclinical data
PK endpoints for phase 1 clinical trials are used to:
- Establish safety in humans
- Determine maximum tolerated dose (MTD) or optimal biological dose (OBD), which are needed to design dosing strategies of Ph2 efficacy studies
→ MTD determined following escalation studies. This allows calculation of the therapeutic index.
→ OBD is more applicable to biologics rather than small molecules
- Some preliminary identification of target interaction or potential off target consequences
Plasma data obtained from the FIH studies are after a single dose administration. The sampling strategy is important so that PK is characterised as accurate as possible to characterise basic PK parameters like Vd, CL, AUC, F, MRT, t1/2, Cmax and Tmax.
Phase 1 trials establish dose safety and determine the strategy for dose escalation studies (single vs multiple ascending dose).
Phase 2 and 3 PK
Phase 2 PK studies establish a relationship between the dose and effect. Dose ranging is used. This can be increasing doses in the same individuals or using different concentrations in different groups. Minimum and maximum effective doses and the therapeutic range are determined. The doses used would not go above the animal MTD, which is why it is important to know this first
Phase 3 PK studies confirm the PK/PD relationship.
These may also identify sources of variation and involve comparative PD and PK.
Compartmental models are used to characterise the PK profile. These help determine variation better than NCA.
- In the case of non-compartmental PK, we only know the concentration at the times measured. Compartmental PK allows us to predict concentrations at other times.
- The number of compartments chosen is based upon the shape of the empirically-defined plasma concentration-time curve.
The PD effect is measured and compared to PK (drug exposure) in phase 2
Sources of variability are identified in phase 3
Good sampling is important but not usually achievable clinically in large scale studies.
Interindividual variability in PK
There is interindividual variability in pharmacokinetics.
During phase 2 and 3 clinical trials, the expected drug response may not be observed in some people. This is because heterogeneity between humans can lead to differences in exposure.
Variation occurs due to intrinsic factors, like sex, age, pregnancy, genetic variation and disease state, as well as extrinsic factors like diet, lifestyle factors (e.g. smoking and drinking) and environmental pollutants.
The diet can affect absorption by affecting gastric emptying. For example, a vegetarian diet prolongs gastric emptying, delaying the absorption and onset of action of paracetamol.
Some compounds from dietary sources can interact with drugs by inducing or inhibiting enzymes. Bergamottin from grapefruit inhibits CYP3A4 in the intestinal wall and liver, reducing first-pass metabolism and so increasing bioavailability and reducing clearance. Broccoli is a known inducer of CYPs, having the opposite effect.
Cigarette smoking causes increased metabolic activity of CYP1A2 and so increases CL of antipsychotic drugs. Olanzapine exposure is 5-fold lower in smokers vs non-smokers, which can lead to failed therapy.
Alcohol consumption can affect gastric emptying. Beverages with low alcohol content, like wine and beer, can speed up gastric emptying, while spirits can slow it down. Chronic consumption of large amounts of alcohol can speed up gastric motility.
Alcohol also affects drug metabolism by inducing CYP2E1. This increases the production of toxic metabolites from isoniazid and of NAPQI from paracetamol, increasing the risk of hepatotoxicity.
Pharmacokinetics in paediatrics
The physiology and biochemistry of children is dynamic and changes constantly in the first months of life, unlike in adults. The changes are not linear.
PK is affected by ontogeny, the origination and development of an organism from the time of fertilization of the egg to adult.
Longitudinal development/maturation processes should be considered during paediatric dose optimisation. You should consider the developmental differences between children and adults and the PK challenges this may cause for your drug.
For example, the contribution of UGT and SULT pathways to paracetamol clearance is different in children compared to adults. Metabolism is initially dominated by the SULT pathway, but there is a gradual shift towards the UGT pathway in adulthood. Understanding changes in enzyme expression will help us understand how Cl and drug disposition change.
Absorption in paediatrics
The gastric pH is neutral in the first week of life, and acidity doesn’t reach adult values until around 2 years.
This protects acid labile drugs, which are degraded in the GIT by the acidic environment. There will be a higher rate of absorption and so bioavailability in children. For example, there is a high bioavailability for beta-lactams like penicillin.
Weak acids become ionised in the neutral environment, so there is a low bioavailability for phenytoin, acetaminophen (paracetamol) and phenobarbital.
Gastric emptying and transit are decreased in children. Delayed stomach emptying means that there is a decreased rate of absorption.
Bile salts are reduced, which reduces the solubility of lipophilic drugs.
Children can have variable hepatic and extrahepatic CYP levels compared to adults, which can affect the extent of first-pass metabolism and therefore bioavailability of the drug. Understanding expression of different enzyme isoforms in children vs adults can help you anticipate differences in first-pass metabolism and absorption.
Paracetamol shows a prolonged absorption half‐life in children under 3 months.
Phenobarbital, sulfonamides and digoxin all have an absorption rate that increases from 3 weeks to 1 year of age.
Distribution in paediatrics
Body water and fat content are redistributed as we age. Water decreases by 20% within the first year and fat increases 4-5 fold.
This directly influences the volume of distribution of fat and water soluble drugs.
In adults, albumin levels are around 40 g/L and alpha-1-acid glycoprotein (AAG) levels are 1 g/L.
Plasma protein levels are often lower in infants compared to older children. HSA levels at birth are ~80% of adult levels and AAG levels are <50% of adult levels.
This means that the concentration of unbound/free drug is higher, so the Vd is higher.
This effect is especially pronounced for highly protein bound drugs.
The drugs have a greater ability to distribute out of the blood. Extensive tissue distribution can lead to an increased half-life.
This can create tissue specific issues, such as CNS delivery due to an immature BBB.
Metabolism in paediatrics
Paediatrics show precise ontogeny patterns in the expression of drug metabolism enzymes.
Different enzymes have different patterns.
CYP3A4 takes around 5 years to reach adult levels. As this is the main drug metabolising enzyme, this impacts the metabolism of many drugs.
Other enzymes develop much faster.
This can directly affect drug clearance. There is a prolonged half-life in children.
This requires age-related dosing regimens, partially for high clearance drugs.
Excretion in paediatrics
The kidneys are functionally immature at birth.
GFR is very low (0.6 – 4 mL/min/1.73m2) compared to normal adult GFR (> 90 mL/min/1.73m2).
Renally cleared drugs will show a progressive decrease in the half-life with ageing as renal function develops.
For drugs primarily excreted via the kidneys, doses have to be adjusted to account for a reduced GFR in children.
Pre-term vs newborn infants show different trajectories of development. There is a difference in the rate of increase in GFR due to the development of CO in ‘at-term’ vs ‘preterm’ neonates.
Pharmacokinetics in the elderly
Ageing is a complex process that may involve both physiological and pathophysiological changes.
The impact of ageing on PK is often confounded by diseases common in the elderly, such as hypertension and diabetes.
Comorbidities that impact the function of major organs involved in ADME processes are common in the elderly. This has to be taken into consideration when thinking about the impact of age on PK properties.
Absorption in the elderly
Interstitial blood flow decreases with age, which could decrease the rate or extent of oral absorption.
Gastric pH increases, becoming more basic, which affects ionisation and solubility of drugs.
Absorbing cells are reduced and gastric emptying is delayed.
However, these factors don’t result in a significant or demonstratable effect on drug absorption in elderly compared to adults.
You need to not only identify potential issues, but also evaluate the impact of this change and how clinically significant it is.
