There is growing interest in Phase I dose-finding studies studying several doses of more than one agent simultaneously. A number of combination dose-finding designs were recently proposed to guide escalation/de-escalation decisions during the trials. The majority of these proposals are model-based: a parametric combination-toxicity relationship is fitted as data accumulates. Various parameter shapes were considered but the unifying theme for many of these is that typically between 4 and 6 parameters are to be estimated. While more parameters allow for more flexible modelling of the combination-toxicity relationship, this is a challenging estimation problem given the typically small sample size in Phase I trials of between 20 and 60 patients. These concerns gave raise to an ongoing debate whether including more parameters into combination-toxicity model leads to more accurate combination selection. In this work, we extensively study two variants of a 4-parameter logistic model with reduced number of parameters to investigate the effect of modelling assumptions. A framework to calibrate the prior distributions for a given parametric model is proposed to allow for fair comparisons. Via a comprehensive simulation study, we have found that the inclusion of the interaction parameter between two compounds does not provide any benefit in terms of the accuracy of selection, on average, but is found to result in fewer patients allocated to the target combination during the trial.

Pharmacokinetic (PK) studies are conducted to learn about the absorption, distribution, metabolism, and excretion processes of an externally administered compound by measuring its concentration in bodily tissue at a number of time points after administration. Two methods are available for this analysis: modeling and non-compartmental. When concentrations of the compound are low, they may be reported as below the limit of quantification (BLOQ). This article compares eight methods for dealing with BLOQ responses in the non-compartmental analysis framework for estimating the area under the concentrations versus time curve. These include simple methods that are currently used, maximum likelihood methods, and an algorithm that uses kernel density estimation to impute values for BLOQ responses. Performance is evaluated using simulations for a range of scenarios. We find that the kernel based method performs best for most situations.

Folate has been proposed to be an efficacious treatment strategy for depression. The mandatory fortification of flour with synthetic folic acid (FA) in over 80 countries has yielded improvements in folate intake; however, depression is still a considerable public health concern. While there are established benefits of FA fortification in reducing risk of neural tube defects, the implications regarding depression are unclear, especially in individuals with certain genetic polymorphisms. Therefore, a systematic review was conducted to examine the effects of folate to treat depression. Following PRISMA guidelines, a systematic review was conducted of electronic databases (PUBMED, Scopus, CINAHL, and Cochrane Library) to identify human clinical trials examining the effects of folate (including FA) supplementation in the management or prevention of depression, the impact on inflammatory markers and if genetic polymorphisms were considered. Ten trials met the inclusion criteria. Seven trials examined effects of either adjunctive FA or L-methylfolate (L-MTHF) supplementation with antidepressants in the management of depression and three examined effects of FA supplementation alone for prevention of depression. No benefit of FA was found compared to placebo (all, p > 0.05). The single L-MTHF trial that explored the interplay of genetic polymorphisms and methylation status found benefit in the Hamilton depression rating scale from adjunctive treatment with 15 mg/day of L-MTHF compared with placebo (−6.8 ± 7.2 vs. −3.7 ± 6.5; p = 0.017) and improvement with L-MTHF for most genetic markers. Currently, there is no evidence to support FA supplementation for the management or prevention of depression. More research is required to determine the efficacy of L-MTHF and folinic acid in certain clinical populations.

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In traditional toxicology trials, pharmacokinetics (PK) is investigated in the satellite group of animals, and the pharmacodynamics (PD) is investigated in the study group of animals. The new blood sampling method of microsampling opens up the opportunity to investigate both PK and PD in the same animals. To avoid excessive burden on the animals from the required blood sampling, sparse sampling schemes are typically used. Motivated by this application, this article introduces a procedure to choose an optimal sparse sampling scheme and sampling time points using non-compartmental methods but which can be applied to further settings beyond this. We discuss how robust designs can be obtained and we apply and evaluate the approach to a range of scenarios to give an example of how it may be implemented. The results are compared to optimal designs for model based PK. Supplementary materials for this article are available online.