The words you are searching are inside this book. To get more targeted content, please make full-text search by clicking here.

www.iajpr.com e 0 Indo American Journal of Pharmaceutical Research, 2015 ISSN NO: 2231-6876 PBPK Modelling, xenobiotics. But use is limited because of large ...

Discover the best professional documents and content resources in AnyFlip Document Base.
Search
Published by , 2016-07-12 20:09:03

PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELLING ...

www.iajpr.com e 0 Indo American Journal of Pharmaceutical Research, 2015 ISSN NO: 2231-6876 PBPK Modelling, xenobiotics. But use is limited because of large ...

Indo American Journal of Pharmaceutical Research, 2015 ISSN NO: 2231-6876

PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELLING: REVOLUTIONISING
DRUG DISCOVERY AND PHARMACOKINETIC STUDIES

R. S. Nikam, V. N. Garge, Dr. V. J. Kadam

BharatiVidyapeeth’s College of Pharmacy, C.B.D. Belapur, Navi Mumbai.

ARTICLE INFO ABSTRACT
Article history Physiologically based pharmacokinetic (PBPK) models are the mathematical expressions that
Received 15/06/2015 predict the drug disposition based upon its physicochemical, physiological and biochemical
Available online properties. This review article discusses the principles and applications of the PBPK
31/07/2015 model.Designing the model for a particular drug and tissue/ organ/ full body is a systematic
process which takes into consideration the physicochemical and biochemical properties of the
Keywords drug, the species involved in the study, route of drug administration and parameters that need
PBPK Modelling, to be included in the model is decided. Steps involved in modelling are designing model
Pharmacokinetic Models, according to its application, setting mathematical equations and validation of model.
Drug Discovery. Accuracy of PBPK model depends upon extent of detailing incorporated in model designing
and hence upon its closeness to real physiology. Considering involvement of tremendous
amount of data and complexity of models, software such as Gastroplus, PK-Sim, MATLAB,
PKQuest etc. are used. PBPK models have great scope for use in the area of Drug Discovery.
They can precisely predict the pharmacokinetics of a particular drug for a particular model.
Hence they are useful in the drug discovery process, for making the personalised medicines,
for prediction of the possible toxicity and carcinogenicity of a particular environmental
xenobiotics. But use is limited because of large amount of data is needed to be processed and
expert personal are required to design such complex models.

Corresponding author

Mr. Rahul S Nikam
Bharati Vidyapeeth‟s College of Pharmacy,
C.B.D. Belapur, Navi Mumbai

[email protected]

8080160885

Please cite this article in press as Mr. Rahul S Nikam et al. Physiologically Based Pharmacokinetic Modelling: Revolutionising Page2450
Drug Discovery and Pharmacokinetic Studies. Indo American Journal of Pharm Research.2015:5(07).

Copy right © 2015 This is an Open Access article distributed under the terms of the Indo American journal of Pharmaceutical
Research, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

INTRODUCTION
Many newly synthesised drug molecules fail to make it to the market place because of poor pharmacokinetic properties. They

are either poorly absorbed or not properly distributed at site of action or are metabolised rapidly and eliminated; which can cost
billions of dollars if failure occur at advance stages of clinical trials. [1] Accurate prediction of pharmacokinetic profile of such newly
synthesised drugs can help drug developers to derive hits from leads. Pharmacokinetics of drug molecules is a complex process and
depend upon many Drug independent (Physiological) and Drug dependent properties. [2] The ability of Physiologically based
pharmacokinetic (PBPK) models to accurately predict pharmacokinetic properties can be useful tool in drug development.

Contact with environmental xenobiotics is unavoidable in this modern world.Constant exposure with these hazardous
pollutants can cause neurotoxicity, genotoxicity and carcinogenicity. [3] Pharmacokinetics of these xenobiotics determines the extent
of toxicity. But health hazard of these pollutants depends upon their concentration at target tissue rather than their concentration in
environment. [4] PBPK models can precisely estimate the target dose.
PBPK models show promise in the fields of Drug Discovery, toxicity studies, Drug interaction studies, Designing personalised
medicines, Animals to human extrapolation of pharmacokinetic data of drugs. However this modelling is very complex and extensive
process. Understanding principles of PBPK modelling is important for designing. This article gives an overview of principles and
applications the model.

Pharmacokinetic Models:
Pharmacokinetic models are mathematical expressions that are used to establish the relation between the drug concentration

in target tissue (which cannot be measured directly) and plasma concentration of drug (which can be analysed). [5]
In the conventional or compartmental models animal body is considered to be composed of two or more theoretical compartments
along which exchange of drug occurs. As these models do not cover detailed physiological process, they are not useful to predict
pharmacokinetics of drugs. [2]

Whereas in Physiological based pharmacokinetic (PBPK models), compartmentalisation is made in a complex way based on
real physiology by putting together similar organs.PBPK models are actually subtype of compartmental models. Only difference is
that PBPK models incorporate great deal of details, hence are more accurate. PBPK models are mechanistic models hence they can be
used for extrapolation of data. Whereas, in compartmental models only interpolation within validated data is permissible. This
advantage proves important when acute studies are extrapolated to predict chronic effects. Furthermore animal data of such acute
toxicity studies of environmental xenobiotics can be extrapolated for humans with PBPK modelling. [2]

History of PBPK models:
Rise and development of PBPK models took place in 20th century. In the 1920s, Haggard wrote the equations for the

relationship between inhaled ether and its concentration in the blood. [6] In the 1930, Teorell described the equations for absorption,
distribution and elimination of drug in the body. [7] Henderson and Haggard (1942) wrote in their several chapters of American
Chemical Society monograph detailed principles of toxicology of inhaled compounds. [8] More detailed PBPK models for inhalation
compounds were deduced Kety (1951), Mapleson (1963) and Riggs (1963). [9, 10] Analogue computers were used by Mapleson
(1963) to solve PBPK equations. [10] In 1966, Brown and Bischoff described the compartmentalisation of body by grouping together
according to appropriate volume, blood flow and pathways to carry out metabolism studies. [11] The analogue computer models for
inhalation compounds were further extended by Fiserova-Bergerova and colleagues (1975, 1979, 1980) to study occupational
environment. [12]

PBPK model development:
Model structure: [13]

PBPK models use the knowledge of physiological processes and physicochemical properties of the drug to predict the
pharmacokinetics of the drug. A schematic structure of a PBPK model is represented as boxes and arrows. Organs and organ systems
are represented as boxes and physiological and clearance processes with arrows. Model consist of two main parts- Physiological
parameters, which are independent of compound and therefore can be applied to any drug and the drug‟s specific ADME properties,
which are applied to each compartment. A general PBPK model as shown in figure 1 consists of various organs with similar
pharmacokinetic processes (e.g. Stomach, Liver and Kidney). The organs with similar pharmacokinetic and physiology are grouped
together. These organs are connected by systemic circulation i.e. arterial and venous blood. (as shown in Fig. 1) Partitioning of drugs
between these compartments is represented differential equations for each compartments. Hence these mathematical equations for
absorption, distribution and elimination accuracy predict the fate of the drug. But this accuracy of model depends upon detailing of the
parameters and in turn that depends upon present knowledge of physiological, physicochemical and biochemical properties of the
drug.

Page2451

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

Model equations: [2]
The mathematical expressions for PBPK model are based on law of mass action. These are mainly four types of equations,

a. Simple Algebraic equations- These are used when quick equilibrium is achieved in the process. Aerosol based drugs are known to
equilibrate quickly between alveoli and inhaled air

b. Linear Differential Equations- Under well stirred hypothesis and linearity of pharmacokinetic processes these equations are used.
c. Non-linear Differential Equations- Some concentration dependent process which tend to saturate such as clearance/ protein

binding/ carrier mediated transport cannot be formulated by linear equations are suitable for non-linear differential equations.
Classic example is hepatic metabolism of certain drugs.
d. Partial Differential Equations- When there is a concentration gradient within organ/ tissue, such tissue or organ is considered to be
made of many such compartments and this model is called as „Dispersion model‟. E.g. when drug has large tissue affinity (Liver
dispersion model), tissue has large physical distribution (Adipose, Skin). In such cases these equations are used.

Fig.1 Structure of PBPK model. Page2452

Estimation of parameters: [13]
Once suitable model is selected is and appropriate mathematical equations are established then various parameters are determined.
a. Drug independent parameters (Physiological parameters)-
Body weight, organ/ tissue weight, tissue/ body fluid volume, cardiac output, perfusion rate, alveolar ventilation rate etc. These

are also known as drug-independent parameters.
b. Drug-dependent parameters-
Drug dependent parameters are further classified as Physicochemical parameters and Biochemical parameters,
I. Physicochemical parameters- Partitioning (Blood-plasma and tissue-plasma), Permeability of drug.
II. Biochemical parameters- Protein binding (binding of drug to blood, plasma and other tissue), Rate of absorption, Maximum

velocity of metabolism and Michaelis affinity constant.
These parameters depend upon physicochemical properties of the drug molecule, hence are called as drug-dependent properties.

Validation of model: [14]
PBPK model is dependent upon various Drug-dependent and drug-independent parameters and these parameters are

subjected to measurement and prediction of errors. Hence once PBPK model is selected and parameters and equations are set, model
must be checked for usefulness i.e. Validation or Evaluation of model. Model evaluation include comparing simulation data with
experimental data as well as Uncertainty, Sensitivity, Variability analysis.

Sources of errors are arising from variation in ethnicity (Asians and Africans have lower CYP3A4 activities, Asians have low
CYP2C19 activity whereas Africans have low CYP2D6 activity), Genetic polymorphism of enzymes and transporters. Within specific
population group variation can arise from age group, gender and disease state.

Various methods for analysis of variability and uncertainty are Monte-Carlo method, Fuzzy simulation and Bayesian Markov
chain Monte Carlo (MCMC) simulation.

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

PBPK Model Types: [15]
There are mainly three types of PBPK models:
a. Based upon Pharmacokinetic process: Model for Absorption, Distribution, Metabolism and Excretion.
b. Whole body PBPK modelling: It is a model that consists of organs, tissues, fluids interconnected by blood circulation.
c. Partial PBPK modelling: Here, only tissue/ organ of interest is considered as separate compartment.

PBPK model for Absorption:
Satisfactory absorption is important aspect of orally active drug. Simple models do not consider effect of food, non-linear

dosing, and improper absorption. Whereas PBPK model can precisely predict absorption of drug in development. Compartmental
absorption and transit (CAT) model was the first PBPK model, which was further developed into Advanced compartmental absorption
and transit (ACAT) model. GastroPlus, the commercial software for PBPK model works on the principle of ACAT. The model divides
intestine into 9 compartments, each having differential equations for absorbed and unabsorbed drug in each compartment.
Amongst these 9 compartments, example of equation of change of drug concentration in stomach (absorption) is,

Where,
dAUND, ST: Amount of drug dissolved in stomach compartment.
DR: Dissolution rate.
GER: Gastric emptying rate.

PBPK model for distribution:
Reversible partitioning of drug between blood and other tissue is known as Distribution. Lipophilic drugs arepartitioned

highly in surrounding tissues (especially fatty tissues) whereas hydrophilic drugs in blood and interstitial fluid. Brain, though it is a
fatty tissue, its distribution is restricted by Blood-Brain-Barrier (BBB). Tissues act as reservoir of drug and slowly release drug in
blood. All these factors are considered in PBPK model to predict and simulate pharmacokinetics of drug.
Differential equation for change of concentration of drug in a tissue (other than lungs and non-eliminating tissue) is,

Where,
dAUND, ST : Rate of change of drug in tissue.
VT : Volume of the tissue.
QART : Blood flow rate in the tissue.
QVEN : Blood flow rate out of the tissue.

: Tissue-Blood partition coefficient.

PBPK model for Metabolism and Elimination:
Metabolism and Elimination are the key pharmacokinetic parameters that determine the fate of the drug. PBPK models

enables to put together factors affecting metabolism and simulate the metabolism of New Chemical Entities (NCEs). PBPK model
equations help predict Hepatobiliary and Renal drug concentration hence in turn drug concentration at site of action. Various
equations for drug and its metabolite concentration in drug metabolising and eliminating organ compartments are used. An example of
such equation [rate of change of drug concentration in the interstitial (IL) liver (L) compartment] is,

Page2453

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

Where,
VLI: Volume of interstitial liver compartment.
QHA: Blood flow to liver from hepatic artery.
QI: Blood flow to liver from splanchic organ i.
QLI: Blood flow out of the liver.
QPV: Portal vein blood flow.
CART : Concentration of the drug in the artery.
Ci : Concentration in any of the splanchnic organs i.
R is the blood-to-plasma concentration ratio.
Ki, p, u: Unbound tissue plasma partition coefficients of the splanchnic organs.
fup, fub, and fu, LI : The fractions of drug unbound inplasma, blood, and liver, respectively.
CLint : Intrinsic clearancepertaining to the diffusion of drug into hepatocytes from or into the interstitialcompartment.

Whole Body PBPK model:
This model is integration of all organ models i.e. connection of tissue, fluids, organs and systems, assuming that all

compartments are well-stirred and perfusion rate limited. Depending upon the purpose of model, organ/ tissue to include in the model
is decided. This means that large number of tissue are included in the model. This level of complexity can pose practicality problems
such as need of large amount of data and information, in turn mathematical complexity and excess computation time.

Partial Body PBPK model:

Depending upon the purpose of the Whole Body PBPK model tissue/ organs to include are decided. Once this basic model is

decided, models for each tissue/ organ compartment is determined. These each tissues/ organs are considered to be single well-stirred

perfusion rate dependent compartments. That is drug is distributed immediately in the whole volume of the tissue and there does not
exist any concentration gradient within the compartment. If such gradient exists within tissue compartment, it is called as “Dispersion
Tissue model”. In the case where membrane permeability limitation within the organ/ tissue occur, a model consists of two well-

stirred compartments is proposed. More complex models consisting of four compartments and maximum up to six compartments have

been devised.

Software used: [2, 16]
Looking at the extensive amount of data to handle and complexity of PBPK models, specialised software are needed for PBPK

modelling. In recent, years several commercial software have become available. Amongst these are;
- Advanced Continuous Simulation Language (ACSL, AEgis Technologies Group Inc.)
- MATLAB (The Mathwork.Inc.)
- STELLA (High Performance Systems.Inc.)
- MATHEMATICA (Wolfram Research.Inc.)
- CMATRIX, SCop and SCiofit programs (Simulation Resource.Inc)
- Gastroplus, a physiologically-based absorption model.
- PKQuest, a free, interactive PBPK software.
- Cloe PK, server based Whole body PBPK model.
- Simcyp, simulates and predicts the population variability of Whole-body kinetics and drug interactions by building virtual

populations and incorporating extensive demographic, physiological, genetic and ethnic variability.
- PK-Sim, from Bayer Technology Services, an integrated whole-body PBPK software.
- acslXtreme, software enables modelling and simulation of continuous dynamic systems and process.
- Berkeley Madonna, a general purpose differential equation solver.
However, expert personals, wide interdisciplinary skills and tools are more important than just software in PBPK model
development.

Applications of PBPK modelling: Page2454
Drug Discovery – Lead Optimisation: [17]

Synthesis of new analogue of hits (lead compounds) with improved potency, selectivity and having desired physicochemical

pharmacokinetic properties by modification of its structure using knowledge of Structure-Activity Relationship (SAR) is called as
“Lead optimisation”. Many compounds fail in the later stage of clinical trials, causing loss of billions of dollars to the company. So to

prevent such costly project failures companies now carry out Drug Metabolism and Pharmacokinetic (DMPK) studies at early stages

of drug discovery from lead generation to candidate selection. These DMPK studies include in vitro metabolism/absorption assays,

animal pharmacokinetic studies. Whole body PBPK model can predict pharmacokinetic shortcomings of lead compounds by data

integration and hypothesis generation.

Cancer Risk Assessment: [18]
Chemical risk assessment is a process in which toxicity data from various species is analysed to predict possible effect on

human upon exposure. This assessment is carried out on the basis of dosimetry (estimating dose at target tissue in test species and its
extrapolation to humans) and mechanistic information of cancer. Using this knowledge of mechanistic progression of cancer and

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

tissue specific dose to cause cancer. PBPK model can precisely predict the safe dose and dose that can cause cancer. This PBPK
model is based on assumption that equivalent target tissue dose will have same effect regardless of species and route.

Predicting Drug-Drug Interactions: [19]
Administering two or more drugs simultaneously can cause drug-drug interaction, which may lead to complete failure of

intended therapy or reaching toxic levels of drug in body. PBPK model can help simulate and predict such possible interactions. There
was an example of study of drug-drug interaction study of rivaroxaban (Factor Xa inhibitor). Drugs that are both P-gp and moderate
CYP3A4 inhibitors showed such an interaction in individuals with varying degrees of renal impairment. PBPK studies suggest the
possibility of interaction and increased exposure of rivaroxaban and bleeding.

Risk assessment from environmental agents in children: [20]
Because of difference in pharmacokinetics of adults and children, they also differ in risk assessment of environmental

toxicants. Metabolism and clearance in neonates is affected by immature hepatic system. PBPK models are designed using empirical
data. But paediatric toxicokinetic data are not usually available. In a study, caffeine and theophylline were used to develop PBPK
model in neonates and adults. Both are CYP 1A2 substrates. The models developed can be used for other CYP 1A2 substrates, for e.g.
aryl amine toxicants.

Personalised medicine: [21]
Different response of patients to a drug is well-known. A patient‟s response to a drug depends on the age, gender, physical

condition, phenotype, or genetic makeup. PBPK models that are linked to mechanistic pharmacodynamic models andincorporating an
individual‟s physiology, enzymology, receptor (or target) expression levels, and polymorphism can predict an appropriate dose for

that individual.

CONCLUSION
PBPK model has proved to have tremendous potential in the area of Drug Discovery, R&D, toxicity studies. Accuracy and

precision of the models depends upon how closely they follow the real physiology. These models have scope for improvement with
increase in our knowledge of physiological processes and underlying mechanism. Currently, PBPK modelling is in its infancy and
hold good promise. Though its use is limited because of large amount of data to be processed and expert personal to design such
complex models. In future, these models can be more and more accurate and precise. Because these models are dependent upon our
current physiological knowledge. These models can also help designing in silico and in vitro models which can help rapid screening of
the drugs. Saving money and lives of animals in preclinical studies. They can prove to be complimentary to theQuantitative Structure
Activity Relationship(QSAR) studies in the drug discovery process. With rapid computation technologies and advance physiological
knowledge in future, PBPK models can become major tool in drug discovery.

Authors’ Statements:
Competing Interests
The authors declare no conflict of interest.

List of Abbreviations:

PBPK models: Physiologically base Pharmacokinetic Models

ADME: Absorption, Distribution, Metabolism, Elimination

CYP 450 : Cytochrome P450 (Hepatic microsomal enzyme)

MCMC :Markov chain Monte Carlo (simulation technique)

CAT : Compartmental Absorption and Transit

ACAT : Advanced Compartmental Absorption and Transit

BBB : Blood-Brain-Barrier

NCE : New Chemical Entity

DMPK studies : Drug Metabolism, Pharmacokinetic studies

ACSL :Advanced Continuous Simulation Language

R&D : Research and Development

QSAR : Quantitative Structure Activity Relationship

REFERENCES Page2455
1) Chapter 1: Sheila Annie Peters. Physiologically based pharmacokinetic (PBPK) modelling and simulations: Principles, methods

and applications in the pharmaceutical industry. New Jersey. John Wiley and Sons; 2012. p. 8.
2) Ivan Nestorov: Whole body pharmacokinetic models. Clin pharmacokinet 2003; 42 (10): 883-908.
3) Hugh Barton, Weihsueh chiu, Robert DeWoskin, Gary Foureman, Kannan Krishnan, John Lipscomb et al.: Approaches for the

application of physiologically based pharmacokinetic (PBPK) models and supporting data in risk assessment.US Environmental
protection agency, Washington, DC; EPA/600/R-05/043F 2006.
4) Fredrik Jonsson, Gunnar Johanson: Bayesian estimation of variability in adipose tissue blood flow in man by physiologically
based pharmacokinetic modelling of inhalation exposure to toluene. Toxicol 2001; 157: 177-193.

www.iajpr.com

Vol 5, Issue 07, 2015. Mr. Rahul S Nikam et al. ISSN NO: 2231-6876

5) Chapter 1: Peter L Bonate. Pharmacokinetic-pharmacodynamic modelling and simulation. San Antonio. Springer; 2006. p. 1.
6) Haggard. H. W: The absorption, distribution and elimination of ethyl ether. II. Analysis of the mechanism of the absorption and

elimination of such a gas or vapour as ethyl ether. J. Biol. Chem. 1924.
7) Teorell. T.: Kinetics of distribution of substances administered to the body. I. The extravascular modes of administration. Arch.

Int. Pharmacodyn., 1937.
8) Henderson, Y., and Haggard, H. W.: Noxions Gases and the Principles of Respiration Influencing their Action. Reinhold

Publishing Corporation, New York, 1943.
9) Kety. S. S.: The theory and applications of the exchange of inert gases at the lungs. Pharmacol. Rev., 1951.
10) Mapleson. W. W.: An electrical analogue for uptake and exchange of inert gases and other agents. J. Appl. Physiol. 1963.
11) Bischoff. K. B. and Brown. R. H.: Drug distribution in mammals. Chem. Engg. Prog. Sym. Series, 1966.
12) Fiserova-Bergerova, V.: Mathematical modelling of inhalation exposure. J. Combust. Toxicol. 1975; 32: 201–210.
13) Francois Bouzom, Kathryn Ball, Nathalie Perdaems, and Bernard Walther: Physiologically based pharmacokinetic (PBPK)

modelling tools: how to fit with our needs?. Biopharm. Drug Dispo. 2012; 33: 55-71.
14) Chapter 8: Sheila Annie Peters. Physiologically-based Pharmacokinetic (PBPK) Modelling and Simulations. Principles, Methods,

and Applications in the Pharmaceutical Industry. New Jersey. John Wiley and Sons; 2012. p. 161-174.
15) Chapter 4, 5, 6, 7: Sheila Annie Peters. Physiologically-based Pharmacokinetic (PBPK) Modelling and Simulations. Principles,

Methods, and Applications in the Pharmaceutical Industry. New Jersey. John Wiley and Sons; 2012. p. 43-158.
16) Chapter 7: Sheila Annie Peters. Physiologically-based Pharmacokinetic (PBPK) Modelling and Simulations. Principles, Methods,

and Applications in the Pharmaceutical Industry. New Jersey. John Wiley and Sons; 2012. p. 158.
17) Sheila Annie Peters, Anna-Lena Ungell & Hugues Dolgos: Physiologically based pharmacokinetic (PBPK) modelling and

simulation: Applications in lead optimization. Current Opinion in Drug Discovery & Development 2009. 12(4): 509-518.
18) Melvin. E. Anderson: Tissue dosimetry and Physiological-based pharmacokinetic modelling, and cancer risk assessment. Cell

biology and Toxicology 1989. 5(4): 405.
19) Joseph A. Grilloa, Ping Zhaoa, Julie Bullocka, Brian P. Bootha, Min Lub et al.: Utility of a physiologically–based

pharmacokinetic (PBPK) modelling approach to quantitatively predict a complex drug–drug–disease interaction scenario for
rivaroxaban during the drug review process: implications for clinical practice. Biopharm. Drug Dispos. 2012. 33: 99–110.
20) Gary G., Dale H., Abel R., Babasaheb S.: Physiologically based pharmacokinetic (PBPK) modelling of caffeine and theophylline
in neonates and adults: Implications for assessing children‟s risk from environmental agents. Journal of toxicology and
environmental health, Part A 2004. 67: 297- 329.
21) Chapter 14: Sheila Annie Peters. Physiologically-based Pharmacokinetic (PBPK) Modelling and Simulations. Principles,
Methods, and Applications in the Pharmaceutical Industry. New Jersey. John Wiley and Sons; 2012. p. 392.

54878478451150625

Page2456

www.iajpr.com


Click to View FlipBook Version