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Publisher Summary This chapter introduces the basic elements of clinical pharmacology models used in describing the time course of disease progress and changes in progress in response to treatment. The simplest model of disease progress assumes that there is no change in disease status during the period of observation. The linear disease progress model assumes a constant rate of change of a biomarker or clinical outcome that reflects the disease status at any time. The onset of drug effect may be delayed by adding an effect compartment to the drug-action part of the model, which is more realistic, by making active drug concentrations at the effect site. Both an offset effect and a slope effect may be combined to describe the changes in disease status. Phenomena such as a drug concentration–effect delay, tolerance, and rebound to both placebo and active treatments can be made using a linear offset model. The nonzero–asymptote model with all three patterns of disease progress influenced by drug effect is also elaborated in the chapter.

The American Course on Drug Development and Regulatory Science and the US National Institutes of Health held a workshop on cell-based immunotherapy on 22 January 2019.

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get t...

Requiring regional or in-country confirmatory clinical trials before approval of drugs already approved elsewhere delays access to medicines in low- and middle-income countries and raises drug costs. Here, we discuss the scientific and technological advances that may reduce the need for in-country or in-region clinical trials for drugs approved in other countries and limitations of these advances that could necessitate in-region clinical studies.

Radically expanding use of real-world data (RWD) and real-world evidence (RWE) holds the potential to substantially impact drug development, pharmaceutical regulation, and payment within health care systems. Central to this is the reconfiguration of data gathering and transformation of data to information, which can be used as evidence for decision making. We discuss applications of this paradigm in the light of recent developments in both the United States and Europe on RWD and RWE.

To provide insight into pharmacological treatment of hyperuricemia we developed a semi‐mechanistic, dynamical model of uric acid (UA) disposition in human. Our model represents the hyperuricemic state in terms of production of UA (rate, PUA), its renal filtration (glomerular filtration rate, GFR) and proximal tubular reabsorption (fractional excretion coefficient, FE). Model parameters were estimated using data from 9 Phase I studies of xanthine oxidase inhibitors (XOI) allopurinol and febuxostat and a novel uricosuric, the selective UA reabsorption inhibitor lesinurad, approved for use in combination with a XOI. The model was qualified for prediction of the effect of patients' GFR and FE on concentration of UA in serum (sUA) and UA excretion in urine and their response to drug treatment, using data from 2 Phase I and 4 Phase III studies of lesinurad. Percent reduction in sUA from baseline by a XOI is predicted to be independent of GFR,FE or PUA. Uricosurics are more effective in underexcreters of UA or patients with normal GFR. Co‐administration of a XOI and an uricosuric agent should be considered for patients with high sUA first in the treatment algorithm of gout before uptitration of XOI. The XOI dose in combination with a uricosuric can be reduced compared to XOI alone for the same target sUA to the degree dependent on patient's GFR and FE. This exposure‐response model of UA can be used to rationally select the best drug treatment option to lower elevated sUA in gout patients under differing pathophysiological situations.

Hoon Young Suh,1 Carl C Peck,2 Kyung-Sang Yu,1 Howard Lee1,3 1Department of Clinical Pharmacology and Therapeutics, College of Medicine, Seoul National University Hospital, Seoul, Korea; 2Department of Bioengineering and Therapeutic Sciences, School of Pharmacy, University of California, San Francisco, CA, USA; 3Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea Abstract: A systematic review was performed to evaluate how the maximum recommended starting dose (MRSD) was determined in first-in-human (FIH) studies with monoclonal antibodies (mAbs). Factors associated with the choice of each MRSD determination method were also identified. PubMed was searched for FIH studies with mAbs published in English between January 1, 1990 and December 31, 2013, and the following information was extracted: MRSD determination method, publication year, therapeutic area, antibody type, safety factor, safety assessment results after the first dose, and number of dose escalation steps. Seventy-nine FIH studies with mAbs were identified, 49 of which clearly reported the MRSD determination method. The no observed adverse effects level (NOAEL)-based approach was the most frequently used method, whereas the model-based approach was the least commonly used method (34.7% vs 16.3%). The minimal anticipated biological effect level (MABEL)- or minimum effective dose (MED)-based approach was used more frequently in 2011–2013 than in 1990–2007 (31.6% vs 6.3%, P=0.036), reflecting a slow, but steady acceptance of the European Medicines Agency’s guidance on mitigating risks for FIH clinical trials (2007). The median safety factor was much lower for the MABEL- or MED-based approach than for the other MRSD determination methods (10 vs 32.2–53). The number of dose escalation steps was not significantly different among the different MRSD determination methods. The MABEL-based approach appears to be safer and as efficient as the other MRSD determination methods for achieving the objectives of FIH studies with mAbs faster. Keywords: MRSD determination method, starting dose in first-in-human study, first-in-human study with monoclonal antibody, MRSD, safety factor

During the last century, particularly the latter half, spectacular progress has been made in improving the health and longevity of people. The reasons are many, but the development of medicines has played a critical role. This report documents and reflects on the impressive contribution that those working in the pharmaceutical sciences have made to healthcare over the past 50 years. It is divided into six sections (drug discovery; absorption, distribution, metabolism, and excretion; pharmacokinetics and pharmacodynamics; drug formulation; drug regulation; and drug utilization), each describing key contributions that have been made in the progression of medicines, from conception to use. A common thread throughout is the application of translational science to the improvement of drug discovery, development, and therapeutic application. Each section has been coordinated by a leading scientist who was asked, after consulting widely with many colleagues across the globe, to identify “The five most influential ideas/concepts/developments introduced by ‘pharmaceutical scientists’ (in their field) over the past 50 years?” Although one cannot predict where the important breakthroughs will come in the future to meet the unmet medical needs, the evidence presented in this report should leave no doubt that those engaged in the pharmaceutical sciences will continue to make their contributions heavily felt. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:4075–4099, 2012

Poor adherence to medicines in clinical trials can undermine the value of the trials; for example, by compromising estimates of the benefits and risks of a medicine. In this article, we highlight such consequences and also discuss approaches to tackle this problem.

The application of physiologically-based pharmacokinetic (PBPK) modeling is coming of age in drug development and regulation, reflecting significant advances over the past 10 years in the predictability of key pharmacokinetic (PK) parameters from human in vitro data and in the availability of dedicated software platforms and associated databases. Specific advances and contemporary challenges with respect to predicting the processes of drug clearance, distribution, and absorption are reviewed, together with the ability to anticipate the quantitative extent of PK-based drug-drug interactions and the impact of age, genetics, disease, and formulation. The value of this capability in selecting and designing appropriate clinical studies, its implications for resource-sparing techniques, and a more holistic view of the application of PK across the preclinical/clinical divide are considered. Finally, some attention is given to the positioning of PBPK within the drug development and approval paradigm and its future application in truly personalized medicine.

Medical oncologists have traditionally been outside the mainstream of internal medicine, with oncology often being a separate department. In addition, there are many large freestanding cancer centres focused exclusively on oncology care. This partial isolation of the oncologist may have contributed to the evolution of diverse approaches to new drug development between oncology and other therapeutic areas. Specifically, the traditional approach to cytotoxic drug development has utilised phase I trials to determine the maximally tolerated dose (MTD) and nonrandomised phase II trials (at the MTD) to measure the rate of (complete and) partial radiographic responses. Thus, phase III has traditionally been the first randomised controlled evaluation. In contrast, other therapeutic areas (including studies of other lethal conditions without effective treatments) have primarily utilised blinded, placebo-controlled randomised trials in phase II to assess efficacy and to explore dose-response relationships.1 Single-arm historically controlled phase II trials are rarely employed outside of oncology.

An expert group met in Leiden to review the state-of-the-art in detecting drug-related safety problems and to review the role of biomarkers and modelling techniques. It was clear that new drugs are not necessarily safer than old drugs, despite much larger clinical trial programs. Larger or longer clinical trials may be unfeasible and postmarketing surveillance is not being undertaken systematically enough to ensure safety. Biomarkers could improve drug safety by detecting drug-related signals early but determining whether the biomarker is on the causal pathway to toxicity is difficult. The maturity and utility of safety-related biomarkers varies among target organ systems. A consortium approach to assimilate a large amount of biomarker-related safety signals incorporating this information into mechanism-based models may provide a useful way forward. However no techniques will ensure that drugs are perfectly safe and communication with the public is required to achieve mutual understanding of benefit risk/balance assessments.

Clinical trial simulations make use of input/output models with covariate effects; the virtual patient population generated for the simulation should therefore display physiologically reasonable covariate distributions. Covariate distribution modeling is one method used to create sets of covariate values (vectors) that characterize individual virtual patients, which should be representative of real subjects participating in clinical trials. Covariates can be continuous (e.g., body weight, age) or categorical (e.g., sex, race). A modeling method commonly used for incorporating both continuous and categorical covariates, the Discrete method, requires the patient population to be divided into subgroups for each unique combination of categorical covariates, with separate multivariate functions for the continuous covariates in each subset. However, when there are multiple categorical covariates this approach can result in subgroups with very few representative patients, and thus, insufficient data to build a model that characterizes these patient groups. To resolve this limitation, an application of a statistical methodology (Continuous method) was conceived to enable sampling of complete covariate vectors, including both continuous and categorical covariates, from a single multivariate function. The Discrete and Continuous methods were compared using both simulated and real data with respect to their ability to generate virtual patient distributions that match a target population. The simulated data sets consisted of one categorical and two correlated continuous covariates. The proportion of patients in each subgroup, correlation between the continuous covariates, and ratio of the means of the continuous covariates in the subgroups were varied. During evaluation, both methods accurately generated the summary statistics and proper proportions of the target population. In general, the Continuous method performed as well as the Discrete method, except when the subgroups, defined by categorical value, had markedly different continuous covariate means, for which, in the authors' experience, there are few clinically relevant examples. The Continuous method allows analysis of the full population instead of multiple subgroups, reducing the number of analyses that must be performed, and thereby increasing efficiency. More importantly, analyzing a larger pool of data increases the precision of the covariance estimates of the covariates, thus improving the accuracy of the description of the covariate distribution in the simulated population.

Drug development can be a science of extrapolation if the use of a drug exposure-response relationship is embraced and implemented through mechanistically oriented pharmacokinetic (PK)-pharmacodynamic (PD) modeling analysis and clinical trial simulation. The traditional requirement of at least 2 adequate and well-controlled phase III studies by the US Food and Drug Administration for drug approval can be waived in certain situations, substantially reducing the resources and time. In this article, the authors introduce a real drug development case where the chance for this exemption was maximized by actively using PK-PD modeling followed by clinical trial simulation, resulting in faster and more economical introduction of a new dosage regimen to patients.

This study was performed to estimate the population pharmacokinetic (PK) parameters of etanercept in pediatric juvenile rheumatoid arthritis (JRA) patients and to compare the steady-state time-concentration profiles between etanercept 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly subcutaneous (SC) regimens by clinical trial simulation. To this end, mixed-effect analysis (NONMEM, Version 5.1) was performed using the etanercept PK database consisting of 69 JRA patients (4-17 years). Based on the population PK parameters obtained herein, a Monte Carlo clinical trial simulation experiment was conducted to compare the PK profiles in 200 virtual JRA patients who randomly received either etanercept 0.4 mg/kg SC twice weekly or 0.8 mg/kg once weekly for 12 weeks. The following population PK model could adequately describe etanercept PK profiles for twice-weekly SC dosing of 0.4 mg/kg: CL/F (L/h)=0.0576 (female) or 0.0772 (male) x (body surface area in m2/1.071)1.41, V/F(L)=7.88 x (body weight in kg/30.8). The means +/- standard deviations of simulated trough concentrations for 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly dosing regimens were 1.58 +/- 1.07 mg/L and 1.92 +/- 1.09 mg/L, respectively. Peaks during 0.8-mg/kg once-weekly dosing (2.92 +/- 1.41 mg/L) were only 11% higher than during 0.4 mg/kg twice-weekly dosing (2.62 +/- 1.23 mg/L). In conclusion, the clinical trial simulation confirmed that 0.8-mg/kg once-weekly and 0.4-mg/kg twice-weekly SC regimens of etanercept are expected to yield overlapping steady-state time-concentration profiles, leading to equivalent clinical outcomes. This has been the basis of the recent Food and Drug Administration approval of the 0.8-mg/kg once-weekly regimen in pediatric patients with JRA.

A 2-day workshop on “Physiologically Based Pharmacokinetics (PBPK) in Drug Development and Regulatory Science” came to a successful conclusion on May 30, 2002, in Washington, DC. More than 120 international participants from the environmental and predominantly pharmaceutical industries, Food and Drug Administration (FDA), and universities attended this workshop, organized by the Center for Drug Development Science, Georgetown University, Washington, DC. The first of its kind specifically devoted to the subject, this intensive workshop, comprising 7 plenary presentations and 10 breakout sessions addressed 2 major objectives: (1) to “define demonstrated and potential contributions of PBPK in drug development and regulatory science,” and (2) to “assess current PBPK methodologies with the identification of their limitations and outstanding issues.” This report summarizes the presentations and recommendations that emerged from the workshop, while providing key references, software, and PBPK data sources in the appendices. The first day was initially devoted to presentations setting the stage and providing demonstrated applications to date. This was followed by breakout sessions that considered further opportunities and limitations, and which extended into Day 2 to deal with developments in methodologies and tools. Although the primary emphasis was on pharmacokinetics, consideration was also given to its integration specifically with mechanism-based pharmacodynamics.

A novel approach for more efficient, economical, and faster clinical evaluation of new drugs is to couple effectiveness data from phase 2 and other studies with a phase 3 single clinical trial (SCT) for regulatory approval. Sanctioned in the Food and Drug Administration Modernization Act (FDAMA), this approach challenges the traditional requirement for two controlled phase 3 trials for approving a new therapy. Academic, industry, legal, and regulatory experts participated in a workshop to define adequate confirmatory evidence of effectiveness to support regulatory approval based on data from an SCT. Participants examined qualities of confirmatory evidence and SCTs and implications of this model for clinical safety information. Acknowledging the evolutionary nature of scientific evidence of effectiveness, participants identified risks and benefits of this approach, concerns of FDA and pharmaceutical companies, and policy changes that may further encourage widespread use of the confirmatory evidence-SCT model. For example, these policy changes include explicit FDA publication of the basis for effectiveness determinations of new drugs, use of end-of-phase 1 industry-regulator meetings for prospective planning of the confirmatory evidence-SCT program, and more use of established pharmacological knowledge to qualify confirmatory evidence biomarkers and surrogate endpoints.

Background Of the potentially survivable US battlefield deaths from 2001 to 2011, 80% to 91% were caused by severe hemorrhage. We subjected minipigs to acute severe blood loss, administered a single dose of 17α-ethynylestradiol-3-sulfate (EE-3-SO4) without resuscitative fluids, and determined survival as well as cardiovascular, biochemical, and physiologic response parameters. Methods Following controlled removal of 60% circulating blood volume over 1 hour, minipigs received EE-3-SO4 at 0, 1, 3, or 5-mg/mL saline per kilogram of body weight in Experiment 1 (n = 25) and 0-, 0.1-, 0.3-, or 1-mg/mL saline per kilogram in Experiment 2 (n = 23). Survival times and response parameters were recorded for the next 6 hours. Results Median survival times of the minipigs receiving 1 mg/kg (257 minutes and 360 minutes) were 1.8 times and 5 times those of the control group (140 minutes and 65 minutes) in Experiments 1 and 2, respectively. For both experiments combined, the log-rank p value was 0.0002, and the number of animals alive at 6 hours was 6 (50%) of 12 in the 1-mg/kg groups versus 0 (0%) of 12 in the control groups. Early increases in glucose, lactate, potassium, and phosphate as well as decreases in bicarbonate and mean arterial pressure correlated with shorter survival times. Conclusion Administration of a single dose of 1-mg/kg EE-3-SO4 in 1-mL/kg of saline following severe hemorrhage increased survival in 60% acutely bled minipigs by 3.5-fold. Slightly elevated blood pressure values, more physiologic values of oxidative phosphorylation parameters, and lower elevations of possible tissue necrosis parameters correlated with longer survival time. These results support the further product development of EE-3-SO4 for the indication of severe hemorrhage when standard resuscitative fluids are not available.

Background From 2001–2011, >80% of potentially survivable United States battlefield deaths were due to severe hemorrhage. We subjected male rats to acute severe blood loss, administered a single dose of 17α-ethynylestradiol-3-sulfate (EE-3-SO4) without resuscitative fluids, and measured survival and also mean arterial pressures (MAP). Methods After controlled removal of 60% circulating blood volume (10–11 mL) over approximately 45 min, rats received EE-3-SO4 at 0 (vehicle controls), 0.1, 0.3, 1.0, or 3.0 mg/kg in 40 μL/100 g BW saline intravenously. MAP was recorded for 40 min after drug administration and survival was recorded for 6 h. Results The dose response curve was bell shaped with optimum survival at 1 mg/kg EE-3-SO4. Median survival times of rats receiving 1 mg/kg (360 min) were approximately 6 times that of the control group (57 min): P = 0.0001. The number of animals alive at 6 h was 16 of 20 (80%) in the 1 mg/kg group versus 0 of 20 (0%) in the control group. Early increases in MAP correlated with longer survival times. Conclusions Administration of a single dose of 1 mg/kg EE-3-SO4 in 0.4 mL/kg of saline after controlled severe hemorrhage increased survival in rats by 6-fold. Partial recovery of blood pressure values correlated with longer survival time. These results, coupled with similar findings in a companion study in minipigs, support the further product development of EE-3-SO4 for: (1) severe hemorrhage when standard resuscitative fluids are not available, and (2) situations in which prolonged transportation periods are required for definitive treatment of the injured.

A completed phase 3 trial result was simulated 100 times on the basis of a simulation model of quetiapine fumarate (Seroquel), an antischizophrenic agent. The simulation was executed by analysts who were completely blinded from results of the actual trial until after the simulations were submitted to the holder of the trial results. Data from two clinical investigations of quetiapine in patients with schizophrenia were analyzed by use of nonlinear mixed effects modeling to derive a population pharmacokinetic- and pharmacodynamic-based simulation model. The time course of quetiapine concentrations was described by use of a one-compartment open linear pharmacokinetic model with first-order absorption and elimination. The combination of an inhibitory maximum effect pharmacodynamic model for the active treatment effect and a linear function of time for the placebo effect characterized the observed time course of change in the Brief Psychiatric Rating Scale. Simulation results were compared with those in the actual trial to evaluate how well the simulations predicted the outcome. The actual trial results for all doses except the placebo group fell within the predicted Brief Psychiatric Rating Scale scores ± 1 SE. Unlike the phase 2 trial, from which the pharmacokinetic/pharmacodynamic model was developed, the placebo group in the actual phase 3 trial showed deterioration of Brief Psychiatric Rating Scale scores with time. We conclude that variable placebo responses observed in short-term studies of schizophrenia provide an inadequate basis for the modeling and simulation of placebo subjects in clinical trials. Knowledge of the range of placebo response observed in other studies may have provided an improved basis for the placebo effect model. The model for active drug produced adequate predictions of the actual trial outcomes. Clinical Pharmacology & Therapeutics (2000) 68, 568–577; doi: 10.1067/mcp.2000.110975

Background A hypnogram shows how sleep travels through its various stages in the course of a night. The sleep stage changes can be quantified to study sedative drug effects. Methods Hypnograms from 21 patients with primary insomnia were collected during a randomized, placebo-controlled crossover study of 20 mg temazepam. A separate daytime session was performed to determine the pharmacokinetics of 20 mg temazepam and its effect on saccadic eye movement and electroencephalogram. A first-order Markov model was developed to describe the probability of sleep stage changes as a function of time after drug intake and time after last sleep stage change. The influence of temazepam concentration on the probability to change sleep stage was incorporated into the model. Results Transitions between sleep stages were profoundly influenced by the time of the night and by the time since the last change of sleep stage. Temazepam reduced the time spent awake. This effect could be attributed to four mechanisms: (1) transition to “deeper” sleep was facilitated, (2) transition to “lighter” sleep was inhibited, (3) regardless of sleep stage, the transition to wake state was inhibited, and (4) return to sleep was facilitated. Daytime sensitivities to temazepam, measured with the surrogate markers saccadic peak velocity and electroencephalogram beta activity, each correlated with one of the transition probabilities influenced by temazepam. Conclusions By the development of a Markov model for these non-ordered six categorical data, the effect of temazepam on the sleep-wake status could be interpreted in terms of known mechanisms for sleep generation and benzodiazepine pharmacology. Clinical Pharmacology & Therapeutics (2000) 68, 175–188; doi: 10.1067/mcp.2000.108669

Two international meetings were convened in 1998 to review the current science of drug development and the potential opportunities to optimize the evaluation of new drugs in humans. This report represents a synopsis of these meetings, and focuses on the current state of knowledge pertaining to drug development, future scientific and technical needs, and the relative merits of various strategies intended to accelerate the clinical development of drugs.

Suboptimal clinical trials and data management are critical concerns to the pharmaceutical industry, where there is increasing pressure to contain costs, drive profits, and expedite drug development. Using data from three completed trials of a central nervous system drug, a collaborative effort between Zeneca Pharmaceuticals and the Center for Drug Development Science at Georgetown University Medical Center is being made to develop computer-assisted simulation models that predict outcomes measures of clinical trials. The objectives for this project are to more fully understand computer-assisted modeling and simulation techniques (including steps and assumptions made), their application in the design of clinical trials, and their potential impact on the drug development process. Using mixed-effects pharmacokinetic/pharmacodynamic modeling and Bayesian techniques, models were built showing a relationship between predicted and measured drug concentrations and between predicted and measured Brief Psychiatric Rating Scale scores. Although the work is ongoing, it has yielded valuable insight into how clinical trial modeling and simulation may contribute to more efficient drug development.

Background and objective quantitative electroencephalographic parameters and saccadic eye movements are frequently used as pharmacodynamic measures of benzodiazepine effect. We investigated the relationship between these measures and the hypnotic effect. Methods The correlation between the pharmacodynamic measures and sleep quality was determined in 21 patients with primary insomnia. The pharmacokinetic-pharmacodynamic relationships were characterized after administration of 20 mg oral temazepam. The hypnotic effect was determined on the basis of polysomnographic sleep recordings and a subjective sleep evaluation questionnaire. Correlations between pharmacodynamic measures and the improvement of sleep were investigated. Results The pharmacokinetic-pharmacodynamic relationships for the parameters derived from electroencephalography and saccadic eye movements showed considerable interindividual variability. Administration of temazepam led to a significant improvement in the objective parameters sleep period efficiency, wake time after sleep onset, and sleep efficiency and in the subjective assessment of sleep quality. No significant correlations were observed between the pharmacokinetic-pharmacodynamic-derived parameters and the improvement in objective or subjective sleep parameters. Conclusion In subjects with primary insomnia the administration of 20 mg oral temazepam results in changes in both the pharmacodynamic measures and in quality of sleep. No individual correlations between the pharmacodynamic measures and quality of sleep were observed. We concluded that the investigated pharmacodynamic measures are of value in the first assessment of clinical efficacy and for the selection of the dose(s) to be investigated in subsequent trials that aim at showing clinical efficacy. However, the conclusive quantification of clinical efficacy should be performed only on the basis of the clinical end point itself. Clinical Pharmacology & Therapeutics (1997) 62, 444–452; doi

Antidepressant drugs are extensively metabolized. Consequently, the biotransformation pattern of antidepressants has an important influence on their clinical properties, i.e., pharmacokinetics, toxicity, drug-drug interactions, side-effect profile and last but not least therapeutic efficacy. It was against this background that a multidisciplinary group of experts discussed the clinical relevance of the rapidly increasing body of knowledge of antidepressant-metabolizing enzymes. The variability of the response of a given individual to an antidepressant is determined genetically and by the environment. Genetic polymorphism of drug-metabolizing enzymes and inhibition by other substrates may affect the enzymatic biotransformation of antidepressants. In vitro assay techniques allow an estimation of the potential variability in clinical response to antidepressants and a reasonable prediction of the drug-drug interaction patterns. The results of in vitro tests should therefore be considered early in the development of an antidepressant as a background for designing clinical studies (treatment schedules and dosing). Physicians should have an understanding of the relevance of genetic polymorphism for clinical practice. Education is needed in order to fill the existing gaps in knowledge about antidepressant-enzyme interactions and their application in daily treatment practice. The information on potential drug interactions determined by genetic polymorphism and based on studies with enzymes should be increasingly contained in drug compendia.

This report derives from the conference on ‘The Integration of Pharmacokinetic, Pharmacodynamic and Toxicokinetic Principles in Rational Drug Development,’ held on April 24–26, 1991 in Arlington, VA. The conference was sponsored by the American Association of Pharmaceutical Scientists, U.S. Food and Drug Administration and American Society for Clinical Pharmacology and Therapeutics. The objectives of the conference were: (1) To identify the roles and the interrelationships between pharmacokinetics (PK), pharmacodynamics (PD) and toxicokinetics (TK) in the drug development process. (2) To evolve strategies for the effective application of the principles of pharmacokinetics, pharmacodynamics and toxicokinetics in drug development, including early clinical trials. (3) To prepare a report on the use of pharmacokinetics and pharmacodynamics in rational drug development as a basis for the development of future regulatory guidelines.

Clinical trial simulations , Clinical trial simulations , کتابخانه دیجیتال جندی شاپور اهواز

Clinical trial simulation (CTS) concepts and techniques comprise a specialized niche in the field of quantitative pharmacology, enabled by advanced pharmacostatistical data analytic and simulation techniques. Since the first demonstrations of the value of CTS in drug development programs, these techniques have been embraced and advanced by both biopharmaceutical developers and regulatory agencies. In this introductory chapter, the editors discuss important trends that have been impacted by CTS, elaborated in more detail in subsequent chapters.

Prior to 1970s, development and regulation of new drugs was devoid of a fully quantitative, pathophysiological conceptual foundation. Malcolm Rowland pioneered, in collaboration with colleagues and friends, our modern understanding of drug clearance concepts, and equipped drug development and regulatory scientists with key investigative tools such as physiologically-based pharmacokinetic (PBPK) modeling, standardized approaches to characterizing drug metabolism, and microdosing. From the 1970s to the present, Malcolm Rowland has contributed to key advances in pharmacokinetics that have had transformational impacts on drug regulatory science. These advances include concepts that have led to the fundamental understanding that mechanistically derived, quantitative variations in drug concentrations, rather than assigned dosage alone, drive pharmacodynamic effects (PKPD)—including disease biomarkers and clinical outcomes. This body of knowledge has transformed drug development and regulatory science theory and practice from naive empiricism to a mechanism/model-based, quantitative scientific discipline. As a result, it is now possible to incorporate pre-clinical in vitro data on drug physico-chemical properties, metabolizing enzymes, transporters and permeability properties into PBPK-based simulations of expected PK distributions and drug–drug interactions in human populations. The most comprehensive application of PK-PD is in the modeling and simulation of clinical trials in the context of model-based drug development and regulation, imbedded in the “learn-confirm paradigm”. Regulatory agencies have embraced these advances and incorporated them into regulatory requirements, approval acceleration pathways and regulatory decisions. These developments are reviewed here, with emphasis on key contributions of Malcolm Rowland that facilitated this transformation.

Challenged with the clearly demonstrated need for highly trained clinical pharmacologists for new drug development and review activities, the FDA Center for Drug Evaluation and Research (CDER) established an internal Staff College. This organizationally unique and innovative unit addressed the educational needs of both the new and the veteran CDER scientists. A multileveled strategy was conceptualized and implemented as described.

This report derived from the dermatological workshop discusses the problems and issues in the development and optimization of topical therapeutic drug products. It provides a clear understanding and differentiation between transdermal and dermal products. The report also discusses the bioavailability/bioequivalence issues for topical therapeutic products.

Background Cerebellar toxicity is a severe, therapy-limiting adverse reaction of cytarabine given in high doses. The Food and Drug Administration received a report of an increased frequency of cerebellar toxicity at the University of Wisconsin Hospital and Clinics after a switch from the product (Cytosar-U) manufactured by The Upjohn Co., Kalamazoo, Mich., to the generic form made by Quad Pharmaceuticals, Inc., Indianapolis, Ind. Purpose To compare the incidence of cerebellar toxicity in Quad-treated patients with Upjohn-treated patients, a record-based cohort study was conducted at the University of Wisconsin Hospital and Clinics between January 1986 and August 1989. Methods The incidence of cerebellar toxicity was studied in 63 leukemia patients according to the manufacturer of the product received (34 Upjohn only, 25 Quad only, and four both manufacturers). The relative risk of cerebellar toxicity was adjusted for other known risk factors. Results Patients in the manufacturer-defined treatment groups did not differ significantly with respect to age, sex, type of leukemia, disease stage, calculated creatinine clearance, presence of abnormal liver function tests, or total dose received. The crude relative risk of cerebellar toxicity comparing the Quad product with the Upjohn product was 5.0 (95% confidence interval = 1.8-13.7). Adjustment for potential confounders did not alter the association. Other risk factors for cerebellar toxicity, independent of manufacturer, were age greater than 50 years, type of leukemia, disease stage, total dose greater than or equal to 20 g/m2, abnormal pretreatment liver function, and reduced creatinine clearance. Conclusion This study found a significantly higher incidence of cerebellar toxicity with high-dose cytarabine manufactured by Quad Pharmaceuticals when compared with the incidence of cerebellar toxicity with the Upjohn product. Further research at independent institutions would be necessary to allow generalization of this finding. In addition, our findings suggest that a dose reduction in high-dose cytarabine therapy may be indicated for patients with reduced glomerular filtration rates.

This workshop, ‘In Vivo Percutaneous Penetration/Absorption’ was held in Washington, DC, on May 1–3, 1989. The first workshop in this series, ‘In Vitro Percutaneous Penetration’, took place in November 1986 (the report of this earlier meeting was published in Pharmaceutical Research , 4 (1987) 265–267). The objectives of the workshop were to review the relevant literature and to address in detail: (1) In vivo percutaneous penetration/absorption methodology; (2) The characteristics of dosage forms designed for application to the skin; (3) Critical factors controlling in vivo drug transport into and across the skin; (4) The use of models in the assessment and evaluation of in vivo percutaneous penetration/absorption; and (5) Bioavailability/bioequivalence considerations for topical drug products. Scientific knowledge and technology are rapidly evolving in the topical and transdermal drug products area. This report focuses on the methodologies available for the measurement of percutaneous penetration in vivo; each scientific approach is discussed briefly followed by advantages and disadvantages of the methodology.

In a separate paper we have pointed out that in addition to safety concerns which strongly suggest the use of concentration-controlled trials (CCTs) for drugs with narrow therapeutic windows, sample size considerations favor the choice of CCTs in many situations. In this paper, we consider ways in which CCTs can be utilized to streamline the drug development process. In particular, a randomized concentration-controlled titration design is proposed for Phase II of drug development. Such a design would facilitate an assessment of efficacy early in drug development, while providing information on concentration-response for a rational choice of dose or concentration in Phase III-Alternative schemes are considered for comparison. Data analysis and dose selection based on CCTs are also discussed.