Search

As biomarkers continue to become an integral part of drug development and decision-making, there are increased expectations for reliable and quantitative assays. Protein biomarker assay results are directly influenced by the calibrator material. The selection of calibrator material presents many challenges that impact the relative accuracy and performance of the assay. There is an industry-wide challenge finding reliable and well-characterized calibrator material with good documentation. Several case studies are presented that demonstrate some of the challenges involved in selecting appropriate calibrators along with the resolutions that were ultimately applied. From these experiences, we present here a set of recommendations for selecting and characterizing calibrator material based on the intended purpose of the assay. Finally, we introduce a commutability approach, based on common clinical chemistry practices, which can be used to demonstrate inter-changeability with calibrator materials across multiple lots and technology platforms for all types of protein biomarker assays.

CD3 bispecific antibody constructs recruit cytolytic T cells to kill tumor cells, offering a potent approach to treat cancer. T cell activation is driven by the formation of a trimolecular complex (trimer) between drugs, T cells, and tumor cells, mimicking an immune synapse. A translational quantitative systems pharmacology (QSP) model is proposed for CD3 bispecific molecules capable of predicting trimer concentration and linking it to tumor cell killing. The model was used to quantify the pharmacokinetic (PK)/pharmacodynamic (PD) relationship of a CD3 bispecific targeting P-cadherin (PF-06671008). It describes the disposition of PF-06671008 in the central compartment and tumor in mouse xenograft models, including binding to target and T cells in the tumor to form the trimer. The model incorporates T cell distribution to the tumor, proliferation, and contraction. PK/PD parameters were estimated for PF-06671008 and a tumor stasis concentration (TSC) was calculated as an estimate of minimum efficacious trimer concentration. TSC values ranged from 0.0092 to 0.064 pM across mouse tumor models. The model was translated to the clinic and used to predict the disposition of PF-06671008 in patients, including the impact of binding to soluble P-cadherin. The predicted terminal half-life of PF-06671008 in the clinic was approximately 1 day, and P-cadherin expression and number of T cells in the tumor were shown to be sensitive parameters impacting clinical efficacy. A translational QSP model is presented for CD3 bispecific molecules, which integrates in silico, in vitro and in vivo data in a mechanistic framework, to quantify and predict efficacy across species. Electronic supplementary material The online version of this article (10.1208/s12248-019-0332-z) contains supplementary material, which is available to authorized users.

With the growing focus on translational research and the use of biomarkers to drive drug development and approvals, biomarkers have become a significant area of research within the pharmaceutical industry. However, until the US Food and Drug Administration’s (FDA) 2013 draft guidance on bioanalytical method validation included consideration of biomarker assays using LC-MS and LBA, those assays were created, validated, and used without standards of performance. This lack of expectations resulted in the FDA receiving data from assays of varying quality in support of efficacy and safety claims. The AAPS Crystal City VI (CC VI) Workshop in 2015 was held as the first forum for industry-FDA discussion around the general issues of biomarker measurements (e.g., endogenous levels) and specific technology strengths and weaknesses. The 2-day workshop served to develop a common understanding among the industrial scientific community of the issues around biomarkers, informed the FDA of the current state of the science, and will serve as a basis for further dialogue as experience with biomarkers expands with both groups.

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model was used for preclinical to clinical translation of inotuzumab ozogamicin, a CD22-targeting antibody-drug conjugate (ADC) for B cell malignancies including non-Hodgkin's lymphoma (NHL) and acute lymphocytic leukemia (ALL). Preclinical data was integrated in a PK/PD model which included (1) a plasma PK model characterizing disposition and clearance of inotuzumab ozogamicin and its released payload N-Ac-γ-calicheamicin DMH, (2) a tumor disposition model describing ADC diffusion into the tumor extracellular environment, (3) a cellular model describing inotuzumab ozogamicin binding to CD22, internalization, intracellular N-Ac-γ-calicheamicin DMH release, binding to DNA, or efflux from the tumor cell, and (4) tumor growth and inhibition in mouse xenograft models. The preclinical model was translated to the clinic by incorporating human PK for inotuzumab ozogamicin and clinically relevant tumor volumes, tumor growth rates, and values for CD22 expression in the relevant patient populations. The resulting stochastic models predicted progression-free survival (PFS) rates for inotuzumab ozogamicin in patients comparable to the observed clinical results. The model suggested that a fractionated dosing regimen is superior to a conventional dosing regimen for ALL but not for NHL. Simulations indicated that tumor growth is a highly sensitive parameter and predictive of successful outcome. Inotuzumab ozogamicin PK and N-Ac-γ-calicheamicin DMH efflux are also sensitive parameters and would be considered more useful predictors of outcome than CD22 receptor expression. In summary, a multiscale, mechanism-based model has been developed for inotuzumab ozogamicin, which can integrate preclinical biomeasures and PK/PD data to predict clinical response.