Science and Quality Assurance, Part 2: PK/QA

Transcription

1 Science and Quality Assurance, Part 2: PK/QA Anthony B. Jones* Quality Assurance, SFBC Taylor, Princeton, NJ 08540, USA Summary For Quality Assurance to be a proactive partner in drug development we need to understand the scientific concepts that define and shape the pharmaceutical process. Drug development can be more easily understood by considering the basic scientific principles governing the numerous scientific disciplines that contribute to producing safe and effective drugs. This article describes the principles that apply to pharmacokinetics, and how these impact study design and data analysis. Copyright # 2005 John Wiley & Sons, Ltd. Key Words: quality assurance; QA; FDA; pharmacokinetics; bioequivalence Science or Quality Assurance? An earlier first article in this series asked the question to what extent should quality assurance (QA) professionals understand the science behind the studies they are auditing? [1]. As cited in that article, the Organization for Economic Co-operation and Development (OECD) document on Principles of Good Laboratory Practice states that individuals appointed to QA functions should have the ability to understand the basic concepts underlying the activities being monitored [2]. The first article explained how the concepts of drug solubility and permeability influence drug development from choice of molecule through to clinical testing. This paper continues from this, and discusses the principles that govern the pharmacokinetic behavior of drugs, to help demystify pharmacokinetics and provide examples of how this knowledge can assist QA. *Correspondence to: A.B. Jones, Quality Assurance, SFBC Taylor, Princeton, NJ 08540, USA. ajones@sfbci. com Pharmacokinetics Pharmacokinetics (PK) can be defined as the study of what the body does to a drug, the science of describing how a drug is absorbed, distributed, metabolized and eliminated by a living organism. Many books have been written to explain pharmacokinetics and the effect that those books have on the reader can be explained by the following simple equation: R u ¼ j RR 1 P Chapter Z c ToC e 2:5 PKt As you have no doubt surmised, the above equation shows that the majority of books on pharmacokinetics become very difficult for the non-specialist reader to understand after the middle of Chapter 1, and do not facilitate the task of grasping the essential concepts. This is unfortunate, as there are simple, fundamental ideas in pharmacokinetics that are easy to comprehend and which hold true in the majority of circumstances. Of course, the subject can be unfathomably complex as well, to the point that even its practitioners lose sight of the basic concepts, which makes it even more valuable to e DOI: /qaj.348

2 298 AB Jones increase the number of informed reviewers of pharmacokinetics work. The underlying principle in pharmacokinetics is that the body will try to get rid of the administered drug, as it is a xenobiotic, a compound that is foreign to the body. To do this, it generally tries to increase the solubility of the drug so that it will be more soluble in urine, increasing its rate of elimination. To achieve this increase in solubility the body needs to add a water-soluble chemical group to the original drug molecule, for example a glucuronide moiety. These water-soluble groups can only be bonded to the drug molecule if the molecule contains a suitable group, typically a hydroxyl function that can be linked to the glucuronide. The body s first move is to introduce such a group through enzymatic oxidation in the liver the so-called Phase 1 metabolism, mediated by the cytochrome P450 enzymes. Once the drug is oxidized and the necessary hydroxyl function is introduced, a second step (Phase 2 metabolism), catalyzed by a different group of enzymes, can attach the water-soluble glucuronide to the drug molecule. The glucuronidated drug metabolite now has a much higher solubility than theparentdrugandwillthereforebemorereadily retained in the aqueous environment of the urine and removed from the body. ADME Fooled! With the body s basic game plan in mind, we can now explore the processes and concepts that govern the administration and subsequent removal of drug from the body. Pharmacokinetics is synonymous with ADME absorption, distribution, metabolism and excretion an acronym commonly used in describing PK studies. It is worth understanding the definition of each of the components of ADME, before tackling some of the other PK concepts: * Absorption: covers all processes from the site of drug administration to the site where drug is measured (usually blood or urine). * Distribution: the reversible transfer of drug between its site of measurement and other sites in the body. * Metabolism: the irreversible loss of drug from the body by chemical reaction of the drug to give a different molecule (Phase 1 and Phase 2 processes described above). * Excretion: the irreversible loss of unchanged drug from the body. * Elimination: the irreversible loss of drug through the processes of excretion and metabolism. Note the emphasis on site of measurement in the above definitions, as traditional pharmacokinetics is conducted using drug concentration measurements in biological fluids that serve as a window into what is happening in the body. For the sake of simplicity in the ensuing discussion, we will use drug concentration in blood to illustrate the application of pharmacokinetics principles. DFCV The easiest way to look at pharmacokinetics is to understand that in the midst of all the equations and complexity there are only four fundamental parameters that we need to be concerned with: * Dose (D): how much drug is administered. * Fraction of dose available (F, where F is a fraction less than 1): how much of the administered dose reaches the blood, also known as the bioavailability of the drug. This is not only dependent on how much drug is absorbed, but also how much is lost during first-pass metabolism on its way to the systemic circulation. * Clearance (Cl): a constant that relates rate of drug elimination to drug concentration expressed in units of flow, volume per unit time. Clearance values can be visualized as the volume of blood completely cleared of drug in a given time, for example a clearance of 25 millilitres (ml) per minute can be thought of as 25 ml of blood being completely cleared of drug every minute. This visualization also illustrates the idea that rate of drug elimination is higher when drug concentrations are higher (yet clearance is a constant) there is more drug present in the 25 ml of blood

3 Science and Quality Assurance, Part that is completely cleared when there is a higher concentration. Drugs with a high clearance will be removed rapidly from the bloodstream by the organs of metabolism or excretion. * Volume of distribution (V): a hypothetical volume in which the dose of drug would have to be dissolved to get the observed blood concentration. The interrelation of these four fundamental parameters gives us the classic pharmacokinetic profile as illustrated in Figure 1. What Goes in Must Come Out The concepts of dose, fraction of dose available, clearance and area under the concentration time curve (AUC) are all related by the following complex equation: what goes in ¼ what comes out Although this looks a little different to the multiexponential equations we normally associate with PK, it is nevertheless just as valid. Looking a little more closely we see: * What goes in ¼ the dose (D) given multiplied by the fraction of dose available (F). * What comes out ¼ the product of the drug clearance process on the blood drug concentrations over time (i.e. the integral of blood concentration). This integral of blood concentration is the area under the concentration time curve (AUC), which is a commonly measured PK parameter used as a measure of the body s exposure to drug. Hence, what goes in ¼ what comes out can be represented mathematically as follows: F Dose ¼ Cl AUC This equation can be easily rearranged to tell us some simple pharmacokinetics truths: * AUC ¼ F Dose=Cl: the AUC depends only on the dose, fraction available and clearance, no other parameters are involved. So, if we see variation in the AUC values between subjects who have been given the same dose, this must be caused either by a variation in fraction available or by a varying clearance (or by experimental error!). AUC F Dose Cl ¼ AUC F Dose Cl Comparing the AUCs from a test and reference (ref) formulation is the basis for estimating bioavailability or relative bioavailability (bioequivalence testing). If the reference is an intravenous (iv) injection and the test administration is the drug given orally, this allows an estimation of the absolute bioavailability (F) of the drug from the oral formulation. The value of F for an intravenous dose is 1, because all of the administered drug is directly available in the blood, and so C max Drug Concentration (ng/ml) AUC 10 t 5 max C C/2 t 1/ Time (hours) Figure 1. The pharmacokinetic profile.

4 300 AB Jones the ratio of AUCs is numerically equivalent to the bioavailability of the drug from the oral formulation. This assumes constant clearance (usually both test and reference are administered in the same subjects) and that the same dose was given by both routes, such that clearance and dose will cancel out in the above equation. Similarly, if we compare AUCs from different oral dosage forms of the same dose in the same subjects we are comparing a ratio of F, and this is the basis of the bioequivalence experiment, the ratio of F is the relative bioavailability. In bioequivalence we use statistical techniques to show that this ratio is sufficiently close to unity for the test and reference formulations. * Cl ¼ F Dose=AUC: after intravenous dosing (F ¼ 1) the clearance can be calculated by dividing the dose given by the measured AUC. The Human Bathtub Of course, human physiology is considerably more complex than a bathtub (unless you are considering one of those spas with the built-in DVD system and floating remote control). The humble bathtub does however have its place in pharmacokinetics as the analogy for volume of distribution. Imagine a tablet of blue dye dropped into the bathtub: after dissolving and being completely mixed, the resulting concentration of dye in the water would be equal to Amount in dye tablet Concentration ¼ Volume of water in bathtub Or, to calculate volume, Amount Volume ¼ Concentration The same is true for a dose of drug given to a subject the resulting drug concentration in blood is equal to the dose given divided by the volume of the human bathtub. This hypothetical volume is known as the volume of distribution (V). It is hypothetical because, for example, a very fat-soluble drug given to a person with a high fat content will partition into the fatty tissue and blood concentrations will be low. This will give a big value for V, far bigger than any actual volume of fluid in the body. The same may be true for a drug that is subject to extensive binding to tissue proteins or other biological molecules that cause a lower observed concentration for a given dose. This effect can be simulated with the bathtub by imagining that some activated charcoal is dropped into the tub. The blue dye will be adsorbed by the charcoal such that its concentration in the water will drop: if we now estimate volume by dividing amount by concentration we will calculate an apparent volume, larger than the volume of the bathtub. Elimination The region of the pharmacokinetics profile after the peak is where the processes of elimination are occurring at a higher rate than the processes of absorption. The classical descriptor of the tail end of the PK profile is the half-life (t 1=2 ), which is an important parameter in drug development. The half-life is the time it takes for the blood concentrations in the terminal phase of the PK profile to drop by one half: this is important because drugs with a half-life that is too short will probably not stay around long enough to have a useful clinical effect. Conversely, drugs with a half-life that is too long may linger in the body to such an extent that positive or negative drug effects could occur for a long time after discontinuing dosing. To understand the concepts behind half-life, one can visualize that this is simply a balance between how widely the drug is distributed and how rapidly it is cleared. Mathematically speaking t 1=2 / V Cl This seems logical a widely distributed drug will be difficult for the organs of elimination to get at, and will subsequently have a long halflife, whereas a drug with a high clearance will be cleared rapidly and will have a short half-life. This can be illustrated by looking at the halflives of the drugs itraconazole and fluconazole

5 Science and Quality Assurance, Part Table 1. Comparison of half-life, clearance and volume of distribution Compound Half-life (h) Clearance (ml/min) Volume of distribution (l/kg) Itraconazole Fluconazole Ratio (itraconazole:fluconazole) Data from Goodman & Gilman s The Pharmacological Basis of Therapeutics [3]. 21 and 32 h, respectively (Table 1). At first glance it might seem that the two drugs have similar PK properties based on their half-life; however, fluconazole has a low clearance and low volume of distribution, whereas itraconazole has a much higher clearance and volume of distribution. Clearly, the two drugs behave very differently in vivo, and this illustrates the benefit of analyzing half-life in terms of clearance and volume of distribution. Diseases or processes that affect volume and clearance will have effects on drug half-life, for example, induction of enzyme systems through smoking may increase clearance and thereby shorten half-life. Half-life also has a role in how we estimate AUC. The part of the AUC that extends beyond the last measured concentration is estimated based on the last measured concentration and the calculated half-life (or its associated elimination rate constant). For drugs with a long t 1/2 a substantial portion of the AUC may be extrapolated in this manner, depending on the length of the period of measurement. The Max s C max and t max are commonly cited PK parameters. C max is simply the observed maximum drug concentration, which depends on both the rate and extent of drug absorption, as well as the drug clearance and volume of distribution. t max is the time at which the maximum drug concentration is observed, and this parameter is used to estimate rate of drug absorption. Accurate estimation of C max and t max is contingent on having sufficient blood sampling points in this region of the pharmacokinetics profile. Complications Of course, there are complications to the simple PK picture painted above. One of the principal complications is known as non-linear pharmacokinetics where, typically, clearance is not constant across different doses. A common example of this would be where the enzymes that metabolize a drug become saturated at higher drug concentrations such that clearance is reduced for higher doses. Knowing the relationship between AUC, dose and clearance, we can see that AUC will increase disproportionately with dose once saturation begins. Some drugs that are subject to saturable metabolism need to be monitored very closely, as the increase in AUC can be dramatic once the enzyme system is saturated, giving the body a significantly greater exposure to drug. This is the case with some of the anti-epileptic medicines, such as phenytoin, where blood concentrations in patients are monitored on a regular basis. BCS Revisited In the first paper on Science in QA [1], the fundamental importance of a drug s solubility and permeability were discussed in relation to the choice of drug molecule and the Biopharmaceutics Classification System (BCS), used to make decisions on the level of equivalence testing necessary for different compounds. Solubility and permeability also have an influence on the pharmacokinetics of drugs, for example, volume of distribution is dependent on the permeability of the drug such that highly permeable, fat soluble, drugs will tend to have a higher volume of distribution, as they can

6 302 AB Jones permeate into the fatty tissues. Similarly, the fraction of dose absorbed from an oral product, F, is dependent on drug solubility at the different ph s encountered in the gut, as a drug that is not soluble will not be well absorbed. However, correlations of solubility and permeability with pharmacokinetics behavior are often confounded by other factors, and clear relationships are difficult to obtain. The BCS system is nevertheless being used to predict pharmacokinetics properties in an area that has revolutionized PK over the last decade the role of transporter molecules in drug ADME. A treatment of this topic is beyond the scope of this paper, but interested readers are referred to a recent publication proposing a BDDCS a Biopharmaceutics Drug Disposition Classification System [4]. This is an area of research which will keep evolving over the coming years and continue to explain and rationalize our pharmacokinetics observations, as well as help predict the in vivo behavior of molecules. The link between basic scientific concepts and the complexities of drug development is well illustrated by this research. PK QA? So, what is in it for us? How does knowledge of pharmacokinetics benefit the QA professional? Firstly, an understanding of the basic PK concepts makes our job so much more interesting. For example, in reviewing tables of AUC data from a drug interaction study we know that the differences in AUCs are due to differences in F or differences in clearance, if the dose is constant. With this knowledge we can understand the conclusions of the report, which may be, for example, that cytochrome p450- mediated clearance is enhanced by a drug interaction. Knowing that half-life is proportional to a ratio of volume of distribution to clearance we can verify that half-lives are reduced accordingly by the drug interaction. In this way we can do so simple reality checking on the report, and do not be surprised to find errors in some conclusions! An illustration of this is the misconception that AUC is dependent on volume of distribution, an error which is often made by less experienced PK analysts. Such an understanding also allows us to review and evaluate pertinent regulatory agency guidance, for example, the recent FDA Guidance on metabolite testing [5]. The more we understand these guidance documents, the better we are at helping in the rational implementation of their proposals. If we are familiar with the basic concepts in PK we can more easily adopt a risk-based approach in assessing PK data. For example, certain points in the pharmacokinetics profile have more influence on the study conclusions than others, and we can pay particular attention if there are problems or reassays involving C max or the last measurable concentration. Clever People Like Complicated Things Being a high-tech, science-driven profession, the pharmaceutical industry is full of intelligent people, some of whom design, conduct and evaluate the pre-clinical and clinical drug development studies. These people are often attracted to spend a greater proportion of their time concentrating on the more complex aspects of the studies the statistical power, the PK models to be used as this is what most satisfies their need for intellectual challenge. The problem is that sometimes nobody is thinking about the simple things. This problem is aggravated by the growing complexity and distractions that we are exposed to in today s workplace, and compounded in a multi-site environment by lack of communication between different departments. QA can play a critical role in this environment, as the group who get to review the entirety of a project. If we can assure that the simple, basic components of study integrity are in place then we can offer a huge service to our colleagues in operations who can be so involved with the minutiae, complexity and time pressures of the study that they overlook these basics. Take bioequivalence studies as an example. As discussed earlier in this article, bioequivalence is demonstrated by comparing a ratio of AUCs

7 Science and Quality Assurance, Part after dosing both test and reference formulations. This ratio equates to a ratio of F (relative bioavailability, bioequivalence) if dose and clearance are equal between administration of test and reference formulations. The assumption of constant clearance is not entirely valid, but we cannot do much about this except control the parameters that influence clearance, as commonly performed in such protocols (control of diet, exercise, concomitant medications, etc.). We can, however, control the dose given, by ensuring that the test and reference formulations contain the same amount of drug, and that the dosing protocol is sufficient to be confident that all subjects take the whole dose. Even if different doses are administered, as long as the pharmacokinetics are linear this can be corrected for during data analysis. When QA are involved in review of the study preparation we can do some simple checks to ensure that dose is equivalent between the treatments to be compared. The following hypothetical example shows how simple things like this can be overlooked. Big Pharmaceuticals Inc. is a global company who had to support one of their flagship products by performing some very large and expensive bioequivalence studies to demonstrate the equivalence of a revised formulation. After completing the study, the preliminary analysis of the results showed that bioequivalence testing using a comparison of AUC values was not favorable to the new formulation. A more detailed analysis was subsequently performed and various data analysis techniques were employed to help squeeze the results into conformance with the bioequivalence requirements. Only after completing data analysis did someone check the dose in the new and old formulations and at this point they realized that the potency (i.e. dose) of the new product was 7.5% lower than that of the reference product. Because the protocol did not state that dose correction would be performed, they could not include a dose-corrected calculation in their regulatory submission at this late stage. By overlooking the fundamental importance of dose in bioequivalence, Big Pharmaceuticals Inc. jeopardized a multi-million dollar project, something that some very simple initial checks could have detected and corrected in the study protocol. In my opinion, due to the evolution of the business climate, these types of seemingly obvious errors may become more frequent in the future. In case anyone is in any doubt about this, the story related above is true this happened to a major pharmaceutical company in 2004! The take-home message from this is that a better understanding of the scientific concepts that underlie study integrity allows us to be better partners in the drug development process, which is, after all, the fundamental role of Quality Assurance. Acknowledgements I would like to thank Dr Christopher Kemper at SFBC Taylor for his detailed review, comments (including Table 1) and informative discussion. References 1. Jones AB. Science and quality assurance: from dose to overdose. Qual Assur J 2004; 8: OECD. GLP Consensus Document: Quality Assurance and GLP, OECD Series on Principles of Good Laboratory Practice and Compliance Monitoring Number 4 (Revised). Environment Directorate, Organisation for Economic Co-operation and Development: Paris, Goodman LS, Limbird LE, Molinoff PB, Ruddon RW, Gilmon AG. Goodman & Gilman s The Pharmacological Basis of Therapeutics (9th edn). McGraw-Hill: New York, Wu CY, Benet LZ. Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res 2005; 22(1): U.S. Department of Health and Human Services, Food and Drug Administration Center for Drug Evaluation and Research. Draft Guidance for Industry: Safety Testing of Drug Metabolites. June 2005.