scholarly journals A Bayesian Adaptive Design for Combination of Three Drugs in Cancer Phase I Clinical Trials

2016 ◽  
Vol 6 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Mourad Tighiouart ◽  
Quanlin Li ◽  
Steven Piantadosi ◽  
Andre Rogatko
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Márcio Augusto Diniz ◽  
Sungjin Kim ◽  
Mourad Tighiouart

A Bayesian adaptive design for dose finding of a combination of two drugs in cancer phase I clinical trials that takes into account patients heterogeneity thought to be related to treatment susceptibility is described. The estimation of the maximum tolerated dose (MTD) curve is a function of a baseline covariate using two cytotoxic agents. A logistic model is used to describe the relationship between the doses, baseline covariate, and the probability of dose limiting toxicity (DLT). Trial design proceeds by treating cohorts of two patients simultaneously using escalation with overdose control (EWOC), where at each stage of the trial, the next dose combination corresponds to the α quantile of the current posterior distribution of the MTD of one of two agents at the current dose of the other agent and the next patient’s baseline covariate value. The MTD curves are estimated as function of Bayes estimates of the model parameters at the end of trial. Average DLT, pointwise average bias, and percent of dose recommendation at dose combination neighborhoods around the true MTD are compared between the design that uses the covariate and the one that ignores the baseline characteristic. We also examine the performance of the approach under model misspecifications for the true dose-toxicity relationship. The methodology is further illustrated in the case of a prespecified discrete set of dose combinations.


2016 ◽  
Vol 8 (2) ◽  
pp. 124-135 ◽  
Author(s):  
Mi-Ok Kim ◽  
Xia Wang ◽  
Chunyan Liu ◽  
Kathleen Dorris ◽  
Maryam Fouladi ◽  
...  

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3310 ◽  
Author(s):  
Kenneth Lundstrom

Self-replicating single-stranded RNA viruses such as alphaviruses, flaviviruses, measles viruses, and rhabdoviruses provide efficient delivery and high-level expression of therapeutic genes due to their high capacity of RNA replication. This has contributed to novel approaches for therapeutic applications including vaccine development and gene therapy-based immunotherapy. Numerous studies in animal tumor models have demonstrated that self-replicating RNA viral vectors can generate antibody responses against infectious agents and tumor cells. Moreover, protection against challenges with pathogenic Ebola virus was obtained in primates immunized with alphaviruses and flaviviruses. Similarly, vaccinated animals have been demonstrated to withstand challenges with lethal doses of tumor cells. Furthermore, clinical trials have been conducted for several indications with self-amplifying RNA viruses. In this context, alphaviruses have been subjected to phase I clinical trials for a cytomegalovirus vaccine generating neutralizing antibodies in healthy volunteers, and for antigen delivery to dendritic cells providing clinically relevant antibody responses in cancer patients, respectively. Likewise, rhabdovirus particles have been subjected to phase I/II clinical trials showing good safety and immunogenicity against Ebola virus. Rhabdoviruses have generated promising results in phase III trials against Ebola virus. The purpose of this review is to summarize the achievements of using self-replicating RNA viruses for RNA therapy based on preclinical animal studies and clinical trials in humans.


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