Biopharmaceutics Classification System and Biopharmaceutics Drug Distribution Classification System are complimentary, not competing, classification systems that aim to improve, simplify, and speed drug development. Although both systems are based on classifying drugs and new molecular entities into four categories using the same solubility criteria, they differ in the criterion for permeability and have different purposes. Here, the details and applications of both systems are reviewed with particular emphasis of their role in drug development.

Individualization of patient drug dosing to maximize efficacy and minimize toxicity is the goal of clinical pharmacology. Here we review the history of drug dosing individualization from early predictions for renally eliminated drugs based on kidney function through the introduction of clearance concepts for metabolic processes, the differentiation of volume of distribution between pharmacokinetics and chemistry, the role of transporters, the unique pharmacokinetic aspects of oral dosing, and the relevance of protein binding to the emergence of pharmacogenomics. The Food and Drug Administration listing of pharmacogenomic markers in approved drug labeling is analyzed with respect to the promise of genomics in terms of picking the right drug for the patient based on genetic information vs selecting or adjusting the dosage regimen based on genetic information: the former resulting in a great advance, whereas the latter has shown less convincing evidence of clinical relevance. Finally, new information on individualized predictive methodologies based on marker drugs for enzymes and transporters is reviewed. We conclude that although individualization of drug dosing will work for most drugs primarily excreted unchanged in the urine, individualization of dosing regimens is not critical for wide-therapeutic-index drugs, whereas for narrow-therapeutic-index drugs predictions are most often more hype than reality, with therapeutic drug monitoring required. However, continuing advances in discovering and validating biomarkers will lead to predictions of pharmacokinetics/pharmacodynamics in the individualized patient that should result in shifting the hype to reality with time.

A number of experimental observations in the late 1960s, early 1970s could not be explained by the pharmacokinetic theory available at that time. For example rats receiving phenobarbital as an enzyme inducing agent exhibited increased elimination of phenylbutazone in vitro in liver microsomes and in vivo in whole animals compared to that observed in non-induced animals. However, for desipramine, although phenobarbital increased elimination in microsomes, no change in plasma disappearance was noted in vivo for this drug between rats induced with phenobarbital and control rats. Similar in vitro–in vivo discordancies were seen with changes in protein binding. The introduction of clearance concepts in the early 1970s by Professor Rowland and others provided the scientific rationale for these apparently contradictory findings and the recognition that clearance, not half-life, was the measure of the body’s ability to eliminate drugs and most importantly that changes in pathology and physiology could be correlated with measures of clearance. Up to that time half-life was well recognized in terms of basic chemical principles as an appropriate measure of the rate of elimination and reflective of changes in the rate of elimination. The difference between chemistry and pharmacokinetics, however, is that in chemistry the volume in which the reaction occurs does not change. In contrast, in pharmacokinetics, disease states and differences in physiology can change the space available in which the drug may distribute in the body. Thus, it was necessary to develop a pharmacokinetic measure of volume that was independent of elimination, i.e., Vss. Now, the relationship between Vss and clearance led to a unique measure of time of drug in the body, the mean residence time. Although this parameter is calculated in all PK programs, very few pharmaceutical scientists know how it can be useful. Very recently, we have shown that the concepts of accumulation, prediction of which is the clinically relevant use for half-life and mean residence time, are flawed and that the appropriate time dependent parameter to predict accumulation has not been previously correctly identified. Finally, when clearance concepts were developed our understanding of the importance of drug transporters was nonexistent. A critical, and generally unrecognized assumption (which is only explicitly stated in Professor Rowland’s seminal 1973 paper), in the development of the theory of clearance is that the unbound drug concentration in the organ of elimination is in a constant equilibrium with the unbound drug concentration in the systemic circulation, where drug concentration measurements are made. Transporter drug–drug and disease interactions may, in fact, change this equilibrium and potentially what we consider as intrinsic clearance, may not be independent of an eliminating organ volume parameter, contrary to what we have been teaching for the past 37 years.

A number of experimental observations in the late 1960s, early 1970s could not be explained by the pharmacokinetic theory available at that time. For example rats receiving phenobarbital as an enzyme inducing agent exhibited increased elimination of phenylbutazone in vitro in liver microsomes and in vivo in whole animals compared to that observed in non-induced animals. However, for desipramine, although phenobarbital increased elimination in microsomes, no change in plasma disappearance was noted in vivo for this drug between rats induced with phenobarbital and control rats. Similar in vitro-in vivo discordancies were seen with changes in protein binding. The introduction of clearance concepts in the early 1970s by Professor Rowland and others provided the scientific rationale for these apparently contradictory findings and the recognition that clearance, not half-life, was the measure of the body's ability to eliminate drugs and most importantly that changes in pathology and physiology could be correlated with measures of clearance. Up to that time half-life was well recognized in terms of basic chemical principles as an appropriate measure of the rate of elimination and reflective of changes in the rate of elimination. The difference between chemistry and pharmacokinetics, however, is that in chemistry the volume in which the reaction occurs does not change. In contrast, in pharmacokinetics, disease states and differences in physiology can change the space available in which the drug may distribute in the body. Thus, it was necessary to develop a pharmacokinetic measure of volume that was independent of elimination, i.e., V(ss). Now, the relationship between V(ss) and clearance led to a unique measure of time of drug in the body, the mean residence time. Although this parameter is calculated in all PK programs, very few pharmaceutical scientists know how it can be useful. Very recently, we have shown that the concepts of accumulation, prediction of which is the clinically relevant use for half-life and mean residence time, are flawed and that the appropriate time dependent parameter to predict accumulation has not been previously correctly identified. Finally, when clearance concepts were developed our understanding of the importance of drug transporters was nonexistent. A critical, and generally unrecognized assumption (which is only explicitly stated in Professor Rowland's seminal 1973 paper), in the development of the theory of clearance is that the unbound drug concentration in the organ of elimination is in a constant equilibrium with the unbound drug concentration in the systemic circulation, where drug concentration measurements are made. Transporter drug-drug and disease interactions may, in fact, change this equilibrium and potentially what we consider as intrinsic clearance, may not be independent of an eliminating organ volume parameter, contrary to what we have been teaching for the past 37 years.

Here I detail the use of measures of permeability rate and solubility in predicting drug disposition characteristics through the utilization of the Biopharmaceutics Drug Disposition Classification System (BDDCS) and the Extended Clearance Classification System (ECCS) as well as the accuracy of the systems in predicting the major route of elimination and the extent of oral absorption of a new small molecule therapeutics. I compare the BDDCS and ECCS with the FDA Biopharmaceutics Classification System (BCS). I also detail the use of the BCS in predicting food effects and the BDDCS in predicting brain disposition of small molecule therapeutics and in validating DILI predictive metrics. This review provides an update of the current status of these classification systems and their uses in the drug development process.

Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have achieved only minimal success. Several studies have shown total administered dose alone or in combination with drug lipophilicity to be correlated with a higher risk of DILI. However, it would be best to have a predictive DILI methodology early in drug development, long before the clinical dose is known. Here we discuss the extent to which Biopharmaceutics Drug Disposition Classification System (BDDCS) defining characteristics, independent of knowing actual drug pharmacokinetics/pharmacodynamics and dose, can be used to evaluate prior published predictive proposals. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity, and that all of the short-lived published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensively metabolized compounds are at higher risk of developing DILI is confirmed, but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs.

Conclusion

Our published analyses suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms, although BDDCS classification itself is not sufficiently predictive. Almost all of the predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs, although some early data with microliver platforms enabling long-enduring metabolic competency show promising results.

Aim

To analyze the late-stage failures of monoclonal antibody drugs. The later a drug fails in development, the more time and expense is incurred by the sponsor.

Methods

We review the late stage, Phase III, failures of 21 monoclonal antibody drugs between 2014 and 2019 using published and publicly available information to characterize the reasons for these failures.

Results

In some cases, the failures are unavoidable due to the lack of adequate science, but in others, we characterize the causes of such failures and recommend how such failures may have been avoided.

Conclusion

By learning from previous mistakes and adhering to the principles and recommendations provided, it is possible to avoid these common pitfalls, increasing the likelihood of success in phase III clinical trials, and thus securing regulatory approval.

Drug transporters are recognized as key players in the processes of drug absorption, distribution, metabolism, and elimination. The localization of uptake and efflux transporters in organs responsible for drug biotransformation and excretion gives transporter proteins a unique gatekeeper function in controlling drug access to metabolizing enzymes and excretory pathways. This review seeks to discuss the influence intestinal and hepatic drug transporters have on pharmacokinetic parameters, including bioavailability, exposure, clearance, volume of distribution, and half-life, for orally dosed drugs. This review also describes in detail the Biopharmaceutics Drug Disposition Classification System (BDDCS) and explains how many of the effects drug transporters exert on oral drug pharmacokinetic parameters can be predicted by this classification scheme.