Concentration-controlled or effect-controlled trials: useful alternatives to conventional dose-controlled trials?

Beyond Population-Level Targets for Drug Concentrations: Precision Dosing Needs Individual-Level Targets that Include Superior Biomarkers of Drug Responses

The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population-level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population-level targets to all patients. Just as "one-dose-fits-all" may be an inappropriate philosophy for drug treatment overall, a "one-target-fits-all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual-level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability.

The right dose for every patient: a key step for precision medicine

Understanding the basis of variability in the response of patients to the dose of a drug and a willingness to vary the dose regimen as well as the choice of drug should be one of the key pillars of precision medicine.

Determining causal exposure-response relationships with randomized concentration-controlled trials

Determining causal effects in exposure-response relationships is an important but also a challenging task since confounding factors that affect both drug exposure and response often exist and lead to confounding biases in causal effect estimation. Randomized concentration control (RCC) trials are designed to eliminate or to reduce the confounding bias. However, statistical issues in the design and analysis of these trials have not been examined closely in the literature. Analysis of dose-exposure relationship may also be affected by confounding factors if they affect dose adjustments. We examined these issues and suggest methodological and practical solutions. In particular, we proposed using instrumental variables (IV) for the estimation of causal effects in both exposure-response and dose-exposure relationships. We also examined the impacts of confounded treatment heterogeneity on the IV estimate for RCC trials. We illustrated these approaches with a trial design scenario showing the importance of considering multiple practical factors that may alter the performance of the IV estimate. The performance of the IV estimates was examined by simulations for a wide range of scenarios. The results showed clear advantages for the IV estimates over routine estimates. Some situations in which the IV estimates may fail were also identified.

Adaptive trials in paediatric development: dealing with heterogeneity and uncertainty in pharmacokinetic differences in children

AIMS

To assess whether an adaptive design in early clinical trials based on the paradigm of variable dosing and controlled exposure can provide better dosing recommendations compared with the standard fixed dose approach.

METHODS

In a clinical trial simulation setting, a paediatric study was simulated using a pharmacokinetic model previously developed for abacavir. Plasma concentrations following the current recommended dose (8 mg kg⁻¹) were taken at standard sampling times, exposures (AUC) were calculated and doses individually adapted to reach the target exposure (i.e. effective exposure in adults). A second round of simulations followed with the adapted doses, and the resulting concentrations were fitted again with the same model. Exposure distributions in both conditions (i.e. fixed dose and controlled exposure) were compared with the target exposure.

RESULTS

The AUC distribution after the current dose resulted in a median exposure of 6.43 mg h l⁻¹ (90th percentile 3.13-10.67 mg h l⁻¹). A total of 61 of 128 subjects showed AUC values either too low or to high compared with the target exposure. After dose adjustment, the median exposure was 6.94 mg h l⁻¹ (5.57-8.25 mg h l⁻¹), and only 14 subjects deviated from the target range.

CONCLUSIONS

Adaptive randomization can be used to optimize dosing regimens in early paediatric clinical trials. The randomization of patients to target exposure rather than dose increases the probability of demonstrating efficacy (i.e. study power) compared with dose-controlled trials. Furthermore, it contributes to further understanding of the role of dose on the total heterogeneity in clinical response.

A systematic review and empirical analysis of the relation between dose and duration of drug action

There is a log-linear relation between the dose and duration of action of drugs with single-compartment pharmacokinetics and direct, reversible mechanisms of action. However, it has been suggested that this relation does not extend to drugs whose metabolites are active or slowly eliminated, drugs with saturable kinetics, and drugs with hit-and-run effects. The purpose of this study is to test this hypothesis and to quantify the relationship by way of a systematic review coupled to an empirical analysis. All issues of 4 clinical pharmacology journals from 1980 to 2005 are hand-searched for articles that present pharmacodynamic response versus time curves for 4 or more different doses. Data on duration of action, dose, and area under the plasma concentration versus time curve from zero to infinity (AUC) are abstracted and analyzed by panel data regression modeling, with within-study fixed effects. Duration of drug action is defined as the time during which a pharmacodynamic effect (or response) exceeds a nominal threshold. The generalized models of all observations from 33 publications, with duration of action as the dependent variable and the logarithm of the dose (or AUC) as the explanatory variable, yield significant log-linear relationships. The regressions for individual studies are correctly specified in 27 cases; there are insufficient data for analysis in 10 studies, and a log-linear specification is deemed inappropriate in 6. Analysis of published dose-ranging studies shows that the duration of action of a drug is directly proportional to the logarithm of dose across a wide range of different drugs, extending a result that was previously documented for very few compounds.

Integrated pharmacokinetics and pharmacodynamics in drug development

Drug development is a complex, lengthy and expensive process. Pharmaceutical companies and regulatory authorities have recognised that the drug development process needs optimisation for efficiency in view of the return on investments. Pharmacokinetics and pharmacodynamics are the two main principles determining the relationship between dose and response. This article provides an update on integrated approaches towards drug development by linking pharmacokinetics, pharmacodynamics and disease aspects into mathematical models. Gradually, a transition is taking place from a rather empirical approach towards a modelling- and simulation-based approach to drug development. The main learning phases should be phases 0, I and II, whereas phase III studies should merely have a confirmatory purpose. In model-based drug development, mechanism-based mathematical models, which are iteratively refined along the path of development, incorporate the accumulating knowledge of the investigational drug, the disease and their mutual interference in different subsets of the target population. These models facilitate the design of the next study and improve the probability of achieving the projected efficacy and safety endpoints. In this article, several theoretical and practical aspects of an integrated approach towards drug development are discussed, together with some case studies from different therapeutic areas illustrating the application of pharmacokinetic/pharmacodynamic disease models at different stages of drug development.

Individualizing drug dosage by using a random intercept linear model

An algorithm for drug dosage individualization is proposed. The algorithm assumes a random intercept linear model for the log of trough-plasma-concentration-to-dosage ratio of the drug at steady-state, and aims at determining an optimum dosage for producing a trough steady-state plasma concentration within a target concentration range. The minimum number of algorithm steps necessary to find the optimum dosage is computed. Computations are illustrated for clozapine, an antipsychotic drug used to treat patients with severe schizophrenia.

Randomized exposure-controlled trials; impact of randomization and analysis strategies

AIMS

In the literature, five potential benefits of randomizing clinical trials on concentration levels, rather than dose, have been proposed: (i) statistical study power will increase; (ii) study power will be less sensitive to high variability in the pharmacokinetics (PK); (iii) the power of establishing an exposure-response relationship will be robust to correlations between PK and pharmacodynamics (PD); (iv) estimates of the exposure-response relationship are likely to be less biased; and (v) studies will provide a better control of exposure in situations with toxicity issues. The main aim of this study was to investigate if these five statements are valid when the trial results are evaluated using a model-based analysis.

METHODS

Quantitative relationships between drug dose, concentration, biomarker and clinical end-point were defined using pharmacometric models. Three randomization schemes for exposure-controlled trials, dose-controlled (RDCT), concentration-controlled (RCCT) and biomarker-controlled (RBCT), were simulated and analysed according to the models.

RESULTS

(i) The RCCT and RBCT had lower statistical power than RDCT in a model-based analysis; (ii) with a model-based analysis the power for an RDCT increased with increasing PK variability; (iii) the statistical power in a model-based analysis was robust to correlations between CL and EC(50) or E(max); (iv) under all conditions the bias was negligible (<3%); and (v) for studies with equal power RCCT could produce either more or fewer adverse events compared with an RDCT.

CONCLUSION

Alternative randomization schemes may not have the proposed advantages if a model-based analysis is employed.

Individualised Cancer Chemotherapy: Strategies and Performance of Prospective Studies on Therapeutic Drug Monitoring with Dose Adaptation

Therapeutic drug monitoring (TDM) is increasingly used in clinical practice for the optimisation of drug treatment. Although pharmacokinetic variability is an established factor involved in the variation of therapeutic outcome of many chemotherapeutic agents, the use of TDM in the field of oncology has been limited thus far. An important reason for this is that a therapeutic index for most anticancer agents has not been established; however, in the last 20 years, relationships between plasma drug concentrations and clinical outcome have been defined for various chemotherapeutic agents. Several attempts have been made to use these relationships for optimising the administration of chemotherapeutics by applying pharmacokinetically guided dosage. These prospective studies, individualising chemotherapy dose during therapy based on measured drug concentrations, are discussed in this review. We focus on the way a target value is defined, the methodologies used for dose adaptation and the way the performance of the dose-adaptation approach is evaluated. Furthermore, attention is paid to the results of the studies and the applicability of the strategies in clinical practice. It can be concluded that TDM may contribute to improving cancer chemotherapy in terms of patient outcome and survival and should therefore be further investigated.

Pharmacokinetics of high-dose chemotherapy

There is considerable variation in the severity of preparative regimen-related toxicity (RRT) in hematopoietic stem-cell transplantation (HSCT). This variation has been recognized to be due, in part, to the wide variation in the pharmacokinetics (PK) of high-dose chemotherapy (HDC). Consequently, therapeutic drug modeling and pharmacokinetic-directed therapy (PKDT) represents an attractive strategy in this setting. Advances in our understanding of drug metabolism, the nature of the active metabolites, and the ability to measure drug concentrations have led to the point where for some agents it is now possible to treat to a given PK end point with a great deal of reliability. In-depth knowledge of the PK and pharmacodynamics (PD) associations of the agents employed in the high-dose setting will make possible more efficient research into preparative regimen dosing intensity and comparisons of different preparative regimens as well as safer HSCT overall. In this review, we discuss PK and PD studies of high-dose cyclosphamide, melphalan, thiotepa, carmustine, cisplatin, carboplatin, paclitaxel, docetaxel, and busulfan.

Positron emission tomography microdosing: a new concept with application in tracer and early clinical drug development

The realisation that new chemical entities under development as drug candidates fail in three of four cases in clinical trials, together with increased costs and increased demands of reducing preclinical animal experiments, have promoted concepts for improvement of early screening procedures in humans. Positron emission tomography (PET) is a non-invasive imaging technology, which makes it possible to determine drug distribution and concentration in vivo in man with the drug labelled with a positron-emitting radionuclide that does not change the biochemical properties. Recently, developments in the field of rapid synthesis of organic compounds labelled with positron-emitting radionuclides have allowed a substantial number of new drug candidates to be labelled and potentially used as probes in PET studies. Together, these factors led to the logical conclusion that early PET studies, performed with very low drug doses-PET-microdosing-could be included in the drug development process as one means for selection or rejection of compounds based on performance in vivo in man. Another important option of PET, to evaluate drug interaction with a target, utilising a PET tracer specific for this target, necessitates a more rapid development of such PET methodology and validations in humans. Since only very low amounts of drugs are used in PET-microdosing studies, the safety requirements should be reduced relative to the safety requirements needed for therapeutic doses. In the following, a methodological scrutinising of the concept is presented. A complete pre-clinical package including limited toxicity assessment is proposed as a base for the regulatory framework of the PET-microdosing concept.

Pharmacokinetic-pharmacodynamic guided trial design in oncology

The application of pharmacokinetic (PK) and pharmacodynamic (PD) modeling in drug development has emerged during the past decades and it is has been suggested that the investigation of PK-PD relationships during drug development may facilitate and optimize the design of subsequent clinical development. Especially in oncology, well designed PK-PD modeling could be extremely useful as anticancer agents usually have a very narrow therapeutic index. This paper describes the application of the current insights in the use of PK-PD modeling to the design of clinical trials in oncology. The application of PK-PD modeling in each separate stage of (pre)clinical drug development of anticancer agents is discussed. The implementation of this approach is illustrated with the clinical development of docetaxel.