A Bayesian adaptive design for cancer phase I trials using a flexible range of doses

Combination L-Glutamine with Gemcitabine and Nab-Paclitaxel in Treatment-Naïve Advanced Pancreatic Cancer: The Phase I GlutaPanc Study Protocol

Advanced pancreatic cancer is underscored by progressive therapeutic resistance and a dismal 5-year survival rate of 3%. Preclinical data demonstrated glutamine supplementation, not deprivation, elicited antitumor effects against pancreatic ductal adenocarcinoma (PDAC) alone and in combination with gemcitabine in a dose-dependent manner. The GlutaPanc phase I trial is a single-arm, open-label clinical trial investigating the safety of combination L-glutamine, gemcitabine, and nab-paclitaxel in subjects (n = 16) with untreated, locally advanced unresectable or metastatic pancreatic cancer. Following a 7-day lead-in phase with L-glutamine, the dose-finding phase via Bayesian design begins with treatment cycles lasting 28 days until disease progression, intolerance, or withdrawal. The primary objective is to establish the recommended phase II dose (RP2D) of combination L-glutamine, gemcitabine, and nab-paclitaxel. Secondary objectives include safety of the combination across all dose levels and preliminary evidence of antitumor activity. Exploratory objectives include evaluating changes in plasma metabolites across multiple time points and changes in the stool microbiome pre and post L-glutamine supplementation. If this phase I clinical trial demonstrates the feasibility of L-glutamine in combination with nab-paclitaxel and gemcitabine, we would advance the development of this combination as a first-line systemic option in subjects with metastatic pancreatic cancer, a high-risk subgroup desperately in need of additional therapies.

Modeling synergism in early phase cancer trials with drug combination with continuous dose levels: is there an added value?

In parametric Bayesian designs of early phase cancer clinical trials with drug combinations exploring a discrete set of partially ordered doses, several authors claimed that there is no added value in including an interaction term to model synergism between the two drugs. In this paper, we investigate these claims in the setting of continuous dose levels of the two agents. Parametric models will be used to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity and efficacy. Trial design proceeds by treating cohorts of two patients simultaneously receiving different dose combinations and response adaptive randomization. We compare trial safety and efficiency of the estimated maximum tolerated dose (MTD) curve between models that include an interaction term with models without the synergism parameter with extensive simulations. Under a selected class of dose-toxicity models and dose escalation algorithm, we found that not including an interaction term in the model can compromise the safety of the trial and reduce the pointwise reliability of the estimated MTD curve.

Phase I trial of Bermekimab with nanoliposomal irinotecan and 5-fluorouracil/folinic acid in advanced pancreatic ductal adenocarcinoma

In this phase I dose-escalation trial, we assess the maximum tolerated dose (MTD) of Bermekimab in combination with Nanoliposomal Irinotecan (Nal-Iri) and 5-Fluorouracil/Folinic Acid (5-FU/FA). Secondarily, we investigate effects on weight, lean body mass, quality-of-life, the gut microbiome composition, inflammatory biomarkers, progression-free survival, and overall survival. This was a single-arm, open-label adaptive Bayesian dose-escalation study of Bermekimab combined with Nal-Iri and 5FU/FA in patients with advanced or locally advanced PDAC who failed gemcitabine-based chemotherapy. 22 patients enrolled between 2017 and 2019. 3 of 21 patients experienced dose-limiting toxicities attributable to the chemotherapy backbone. 58% (10/17) of patients exhibited weight stability. Physical performance status was preserved among all subjects. Patients reported improvements in quality-of-life metrics via QLQ-PAN26 questioner (-3.6, p = 0.18) and functional well-being (1.78, p = 0.02). Subjects exhibited a decrease in inflammatory cytokines, notably, vascular endothelial growth factor (-0.86, p = 0.017) with Bermekimab. Bermekimab treatment was associated with an increased abundance of gut health-promoting bacterial genera Akkermansia, with 3.82 Log2-fold change from baseline. In sum, Bermekimab is safe to be used in conjunction with Nal-Iri and 5-FU/FA chemotherapy. This benign toxicological profile warrants further Phase I/II investigation of Bermekimab in combinatorial strategies, and the impact of anti-IL-1α antibodies on the gut microbiome.Clinical trials registration: NCT03207724 05/07/2017.

Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity

Vaccination is a key tool to reduce global disease burden. Vaccine dose can affect vaccine efficacy and toxicity. Given the expense of developing vaccines, optimising vaccine dose is essential. Mathematical modelling has been suggested as an approach for optimising vaccine dose by quantitatively establishing the relationships between dose and efficacy/toxicity. In this work, we performed simulation studies to assess the performance of modelling approaches in determining optimal dose. We found that the ability of modelling approaches to determine optimal dose improved with trial size, particularly for studies with at least 30 trial participants, and that, generally, using a peaking or a weighted model-averaging-based dose–efficacy relationship was most effective in finding optimal dose. Most methods of trial dose selection were similarly effective for the purpose of determining optimal dose; however, including modelling to adapt doses during a trial may lead to more trial participants receiving a more optimal dose. Clinical trial dosing around the predicted optimal dose, rather than only at the predicted optimal dose, may improve final dose selection. This work suggests modelling can be used effectively for vaccine dose finding, prompting potential practical applications of these methods in accelerating effective vaccine development and saving lives.

A nonparametric Bayesian method for dose finding in drug combinations cancer trials

We propose an adaptive design for early-phase drug-combination cancer trials with the goal of estimating the maximum tolerated dose (MTD). A nonparametric Bayesian model, using beta priors truncated to the set of partially ordered dose combinations, is used to describe the probability of dose limiting toxicity (DLT). Dose allocation between successive cohorts of patients is estimated using a modified continual reassessment scheme. The updated probabilities of DLT are calculated with a Gibbs sampler that employs a weighting mechanism to calibrate the influence of data vs the prior. At the end of the trial, we recommend one or more dose combinations as the MTD based on our proposed algorithm. We apply our method to a Phase I clinical trial of CB-839 and Gemcitabine that motivated this nonparametric design. The design operating characteristics indicate that our method is comparable with existing methods.

A Bayesian Adaptive Design in Cancer Phase I Trials Using Dose Combinations with Ordinal Toxicity Grades

We propose a Bayesian adaptive design for early phase drug combination cancer trials incorporating ordinal grade of toxicities. Parametric models are used to describe the relationship between the dose combinations and the probabilities of the ordinal toxicities under the proportional odds assumption. Trial design proceeds by treating cohorts of two patients simultaneously receiving different dose combinations. Specifically, at each stage of the trial, we seek the dose of one agent by minimizing the Bayes risk with respect to a loss function given the current dose of the other agent. We consider two types of loss functions corresponding to the Continual Reassessment Method (CRM) and Escalation with Overdose Control (EWOC). At the end of the trial, we estimate the MTD curve as a function of Bayes estimates of the model parameters. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD by comparing this design to the one that uses a binary indicator of DLT. The methodology is further adapted to the case of a pre-specified discrete set of dose combinations.

A phase I study of sirolimus in combination with metronomic therapy (CHOAnome) in children with recurrent or refractory solid and brain tumors

BACKGROUND/PURPOSE

To determine the maximum tolerated dose, toxicities, and response of sirolimus combined with oral metronomic therapy in pediatric patients with recurrent and refractory solid and brain tumors.

PROCEDURE

Patients younger than 30 years of age with recurrent, refractory, or high-risk solid and brain tumors were eligible. Patients received six-week cycles of sirolimus with twice daily celecoxib, and alternating etoposide and cyclophosphamide every three weeks, with Bayesian dose escalation over four dose levels (NCT01331135).

RESULTS

Eighteen patients were enrolled: four on dose level (DL) 1, four on DL2, eight on DL3, and two on DL4. Diagnoses included solid tumors (Ewing sarcoma, osteosarcoma, malignant peripheral nerve sheath tumor, rhabdoid tumor, retinoblastoma) and brain tumors (glioblastoma multiforme [GBM], diffuse intrinsic pontine glioma, high-grade glioma [HGG], medulloblastoma, ependymoma, anaplastic astrocytoma, low-grade infiltrative astrocytoma, primitive neuroectodermal tumor, nongerminomatous germ cell tumor]. One dose-limiting toxicity (DLT; grade 4 neutropenia) was observed on DL2, two DLTs (grade 3 abdominal pain and grade 3 mucositis) on DL3, and two DLTs (grade 3 dehydration and grade 3 mucositis) on DL4. The recommended phase II dose of sirolimus was 2 mg/m² (DL3). Best response was stable disease (SD) in eight patients, and partial response (PR) in one patient with GBM. A patient with HGG was removed from the study with SD and developed PR without further therapy. Western blot analysis showed inhibition of phospho-S6 kinase in all patients during the first cycle of therapy.

CONCLUSION

The combination of sirolimus with metronomic chemotherapy is well tolerated in children. A phase II trial of this combination is ongoing.

Dose Finding for Drug Combination in Early Cancer Phase I Trials using Conditional Continual Reassessment Method

We describe a dose escalation algorithm for drug combinations in cancer phase I clinical trials. Parametric models for describing the association between the doses and the probability of dose limiting toxicity are used assuming univariate monotonicity of the dose-toxicity relationship. Trial design proceeds using the continual reassessment method, where at each stage of the trial, we seek the dose of one agent with estimated probability of toxicity closest to a target probability of toxicity given the current dose of the other agent. A Bayes estimate of the maximum tolerated dose (MTD) curve is proposed at the conclusion of the trial for continuous doses or a set of MTDs is determined in the case of discrete dose levels. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD under various model generated scenarios and misspecification. The method is further assessed for varying algorithms enrolling cohorts of two and three patients receiving different doses and compared to previous approaches such as escalation with overdose control and two-dimensional design.