Explaining in-vitro to in-vivo efficacy correlations in oncology pre-clinical development via a semi-mechanistic mathematical model.

In-vitro to in-vivo correlations (IVIVC), relating in-vitro parameters like IC50 to in-vivo drug exposure in plasma and tumour growth, are widely used in oncology for experimental design and dose decisions. However, they lack a deeper understanding of the underlying mechanisms. Our paper therefore focuses on linking empirical IVIVC relations for small-molecule kinase inhibitors with a semi-mechanistic tumour-growth model.

Radius additivity score: a novel combination index for tumour growth inhibition in fixed-dose xenograft studies.

The effect of combination therapies in many cancers has often been shown to be superior to that of monotherapies. This success is commonly attributed to drug synergies. Combinations of two (or more) drugs in xenograft tumor growth inhibition (TGI) studies are typically designed at fixed doses for each compound.

Skipping a pillar does not make for strong foundations: Pharmacokinetic-pharmacodynamic reasoning behind the shape of dose-response relationships in oncology.

Dose-response analysis is often applied to the quantification of drug-effect especially for slowly responding disease end points where a comparison is made across dose levels after a particular period of treatment. It has long been recognized that exposure - response is more appropriate than dose-response. However, trials necessarily are designed as dose-response experiments.

Association between radiotherapy protocol variations and outcome in the CONVERT trial.

Background: Radiotherapy quality assurance (QA) is integral to radiotherapy delivery. Here we report comprehensive contouring, dosimetry, and treatment delivery QA, describe protocol compliance, and detail the impact of protocol variations on acute grade ≥3 toxicity, progression free survival (PFS), and overall survival (OS) in the phase III CONVERT trial.

Materials/methods: Radiotherapy planning data from one hundred randomly selected patients were requested.

Determining bioequivalence possibilities of long acting injectables through population PK modelling.

Long acting injectables (LAI) products are a popular intervention for treating a number of chronic conditions, with their long drug release reducing the administration frequency and thus improving patient adherence. The extended release, however, can provide a major challenge to bioequivalence (BE) testing since the long absorption half-life results in a long washout period, meaning that a traditional BE study can be many months or years in length. The unique PK profile for LAI products also means that it is critical to have appropriate metrics to summarise the plasma concentration profile.

Exploring a model-based analysis of patient derived xenograft studies in oncology drug development.

Purpose: To assess whether a model-based analysis increased statistical power over an analysis of final day volumes and provide insights into more efficient patient derived xenograft (PDX) study designs.

Methods: Tumour xenograft time-series data was extracted from a public PDX drug treatment database. For all 2-arm studies the percent tumour growth inhibition (TGI) at day 14, 21 and 28 was calculated.

The spindle assembly checkpoint and speciation.

A mechanism is proposed by which speciation may occur without the need to postulate geographical isolation of the diverging populations. Closely related species that occupy overlapping or adjacent ecological niches often have an almost identical genome but differ by chromosomal rearrangements that result in reproductive isolation. The mitotic spindle assembly checkpoint normally functions to prevent gametes with non-identical karyotypes from forming viable zygotes.

A simple model of a growing tumour.

This paper presents the CellCycler, a model of a growing tumour which aims to simulate and predict the effect of treatment on xenograft studies or in the clinic. The model, which is freely available as a web application, uses ordinary differential equations (ODEs) to simulate cells as they pass through the phases of the cell cycle. However the guiding philosophy of the model is that it should only use parameters that can be observed or reasonably well approximated.

Resistance models to EGFR inhibition and chemotherapy in non-small cell lung cancer via analysis of tumour size dynamics.

Purpose: Imaging time-series data routinely collected in clinical trials are predominantly explored for covariates as covariates for survival analysis to support decision-making in oncology drug development. The key objective of this study was to assess if insights regarding two relapse resistance modes, de-novo (treatment selects out a pre-existing resistant clone) or acquired (resistant clone develops during treatment), could be inferred from such data.

Methods: Individual lesion size time-series data were collected from ten Phase III study arms where patients were treated with either first-generation EGFR inhibitors (erlotinib or gefitinib) or chemotherapy (paclitaxel/carboplatin combination or docetaxel).

Complex versus simple models: ion-channel cardiac toxicity prediction.

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model was conducted.

Model based analysis of the heterogeneity in the tumour size dynamics differentiates vemurafenib, dabrafenib and trametinib in metastatic melanoma.

Purpose: Explore the heterogeneity in dynamics of tumour response to vemurafenib, dabrafenib and trametinib using routinely collected clinical trial imaging data.

Methods: Time-series imaging data from the phase III studies of vemurafenib, dabrafenib and trametinib were collected through a data repository. A mathematical model based on basic mechanisms of tumour growth was placed within a statistical modelling framework to analyse the data.

On the relationship between tumour growth rate and survival in non-small cell lung cancer.

A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-points.

Optimizing Clinical Drug Product Performance: Applying Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid.

The aim of Biopharmaceutics Risk Assessment Roadmap (BioRAM) and the BioRAM Scoring Grid is to facilitate optimization of clinical performance of drug products. BioRAM strategy relies on therapy-driven drug delivery and follows an integrated systems approach for formulating and addressing critical questions and decision-making (J Pharm Sci. 2014,103(11): 3777-97).

A new classifier-based strategy for in-silico ion-channel cardiac drug safety assessment.

There is currently a strong interest in using high-throughput in-vitro ion-channel screening data to make predictions regarding the cardiac toxicity potential of a new compound in both animal and human studies. A recent FDA think tank encourages the use of biophysical mathematical models of cardiac myocytes for this prediction task. However, it remains unclear whether this approach is the most appropriate.

The biopharmaceutics risk assessment roadmap for optimizing clinical drug product performance.

The biopharmaceutics risk assessment roadmap (BioRAM) optimizes drug product development and performance by using therapy-driven target drug delivery profiles as a framework to achieve the desired therapeutic outcome. Hence, clinical relevance is directly built into early formulation development. Biopharmaceutics tools are used to identify and address potential challenges to optimize the drug product for patient benefit.

A pharmacodynamic model of Aurora kinase inhibitors in the spindle assembly checkpoint.

Arguably the most dramatic phase in the cell cycle is mitosis, during which replicated chromosomes are sorted into two distinct sets. Aurora kinases are central to the accurate segregation of chromosomes during mitosis. Consequently, they have been selected as possible targets for cancer therapy.