Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability.

Pairwise-based methods such as the free energy perturbation (FEP) method have been widely deployed to compute the binding free energy differences between two similar host-guest complexes. The calculated pairwise free energy difference is either directly adopted or transformed to absolute binding free energy for molecule rank ordering. We investigated, through both analytic derivations and simulations, how the selection of pairs in the experiment could impact the overall prediction precision. Our studies showed that (1) the estimated absolute binding free energy ( ΔG^ ) derived from calculated pairwise differences (ΔΔG) through weighted least squares fitting is more precise in prediction than the pairwise difference values when the number of pairs is more than the number of ligands and (2) prediction precision is influenced by both the total number of pairs and the specifically selected pairs, the latter being critically important when the number of calculated pairs is limited. Furthermore, we applied optimal experimental design in pair selection and found that the optimally selected pairs can outperform randomly selected pairs in prediction precision. In an illustrative example, we showed that, upon weighing ligand structure similarity into design optimization, the weighted optimal designs are more efficient than the literature reported designs. This work provides a new approach to assess retrospective pairwise-based prediction results, and a method to design new prospective pairwise-based experiments for molecular lead optimization. © 2019 Wiley Periodicals, Inc.

Amine promiscuity and toxicology analysis.

Drug discovery programs often face challenges to obtain sufficient duration of action of the drug (i.e. seek longer half-lives). If the pharmacodynamic response is driven by free plasma concentration of the drug then extending the plasma drug concentration is a valid approach. Half-life is dependent on the volume of distribution, which in turn can be dependent upon the ionization state of the molecule. Basic compounds tend to have a higher volume of distribution leading to longer half-lives. However, it has been shown that bases may also have higher promiscuity. In this work, we describe an analysis of in vitro pharmacological profiling and toxicology data investigating the role of primary, secondary, and tertiary amines in imparting promiscuity and thus off-target toxicity. Primary amines are found to be less promiscuous in in vitro assays and have improved profiles in in vivo toxicology studies compared to secondary and tertiary amines.

Development of a sensitive LC-MS/MS assay to support human microdose study for an oral agonist of the GLP-1 receptor.

Aim: The purpose of this work was to determine the feasibility of supporting a clinical microdose study for PF-06882961 (danuglipron), an oral small molecule agonist of the GLP-1 receptor, by LC-MS/MS. Methodology: Statistical instrument parameter optimization using response surface methodology was employed to develop a LC-MS/MS method for the analyte, PF-06882961. Results: An LC-MS/MS method was developed and validated to support a proof of concept microdose pharmacokinetics preclinical study in monkeys, administered PF-06882961 (0.005 mg total, average dose = 0.0007 mg/kg) via intravenous bolus injection. Conclusion: The present study demonstrated the feasibility of analyzing human microdose plasma samples for PF-06882961 by LC-MS/MS, instead of accelerator mass spectrometry, thereby reducing cost and eliminating synthesis and exposure to 14C labeled material.

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A Data Driven Strategy and Case Study for Implementation of Singlicate Analysis in Ligand Binding Assays Used for PK Quantitation.

Duplicate analysis has been a conventional practice in the industry for ligand-binding assays (LBA), particularly for plate-based platforms like Enzyme-linked immunosorbent assay (ELISA) and Meso Scale Discovery (MSD) assays. Recent whitepapers and guidance have opened a door to exploring the implementation of single-well (singlicate) analysis approach for LBAs. Although the bioanalytical industry has actively investigated the suitability of singlicate analysis, applications in supporting regulated LBA bioanalysis are limited. The primary reason for this limitation is the absence of appropriate strategy to facilitate the transition from duplicate to singlicate analysis. In this paper we present the first case study with our data-driven approach to implement singlicate analysis in a clinical pharmacokinetics (PK) plate based LBA assay with ISR data. The central aspect of this strategy is a head-to-head comparison with Precision and Accuracy assessment in both duplicate and singlicate formats as the initial stage of assay validation. Subsequently, statistical analysis is conducted to evaluate method variability in both precision and accuracy. The results of our study indicated that there was no impactful difference between duplicate vs singlicate, affirming the suitability of singlicate analysis for the remaining steps of PK assay validation. The validation results obtained through singlicate analysis demonstrated acceptable assay performance characteristics across all validation parameters, aligning with regulatory guidance. The validated PK assay in singlicate has been employed to support a Phase I study. The appropriateness of singlicate analyses is further supported by initial Incurred Sample Reanalysis (ISR) data in which 90.1% of ISR samples fall within the acceptable criteria.

Feasibility of singlicate-based analysis in bridging ADA assay on Meso-Scale Discovery platform: comparison with duplicate analysis.

Aim: To investigate the feasibility of singlicate analysis in anti-drug antibody (ADA) assay by comparing performance characteristics for assays qualified in duplicate and singlicate formats. Materials & methods: We employed modeling to assess and quantify the impact of singlicate to cut point factor (CPF) in scenarios with the duplicate precision from 1-20% and the proportion of well-to-well variance to overall assay variance from 0.01-0.90. The impact to CPF by singlicate is marginal if the well-to-well coefficient of variation is <10% and represents <25% of the overall variability. Results & conclusion: The assay parameters including sensitivity, precision, selectivity, drug and target tolerance were comparable between singlicate and duplicate based assays. Our results suggested the minimal impact of singlicate analysis on ADA assay with good duplicate precision. The study provided additional supportive evidence that the singlicate-based analysis is feasible in ADA ligand binding assays.

Fit-for-Purpose Validation and Establishment of Assay Acceptance and Reporting Criteria of Dendritic Cell Activation Assay Contributing to the Assessment of Immunogenicity Risk.

Validation of key analytical and functional performance characteristics of in vitro immunogenicity risk assessment assays increases our confidence in utilizing them for screening biotherapeutics. Herein, we present a fit-for-purpose (FFP) validation of a dendritic cell (DC) activation assay designed to assess the immunogenicity liability of protein biotherapeutics. Characterization of key assay parameters was achieved using monocyte-derived DCs (MoDCs) treated with cell culture medium only (i.e., background control (BC)), keyhole limpet hemocyanin (KLH) as system positive control (SPC), and 2 therapeutic monoclonal antibodies (mAbs) with known clinical immunogenicity profiles (bococizumab and TAM163) as therapeutic controls (TCs). In the absence of established validation guidelines for primary cell-based assays, the present DC activation assay was validated using a novel FFP approach which allows more flexibility in selection of validation parameters and designing of experiments based on the intended use of the assay. The present FFP validation allowed us to understand the impact of experimental variables on assay precision, develop a clear concise readout for DC activation results, establish a reliable response threshold to define a result as a positive DC activation response, and define in-study donor acceptance criteria and cohort size. FFP validation of this DC activation assay indicated that the assay is sufficient to support its context of use, a preclinical immunogenicity risk management tool.

Criteria to Reevaluate Anti-drug Antibody Assay Cut Point Suitability in the Target Population.

After tier 1 and 2 cut points for anti-drug antibody (ADA) assays are derived during pre-study assay validation in a population, there is a need to verify the continued appropriateness of the previously derived cut points during sample analysis in the same or different populations, per FDA guidance (US HHS, FDA, CDER, CBER, 2019). Proper sample size-dependent criteria with statistical underpinning were derived and presented in this technical note to aid in assessing the appropriateness of tier 1 and tier 2 cut points, respectively.

Evaluation of Fraction Unbound Across 7 Tissues of 5 Species.

Binding to various tissues and species is frequently assessed in drug discovery and development to support safety and efficacy studies. To reduce time, cost, and labor requirements for binding experiments, we conducted a large comparison study to evaluate the correlation of fraction unbound (fu) across 7 tissues of 5 species, including white adipose, brain, heart, kidney, liver, lung, and skeletal muscle of mouse, rat, dog, monkey, and human. The results showed that there were no significant species differences of fu for tissue binding, and a single-species (e.g., rat) tissue fu can be used as a surrogate for binding in other species. Cross-tissue comparison indicated that brain, heart, liver, and muscle had quite similar fu values; rat liver binding can be used as a surrogate for binding of the other 3 tissues without any scaling factors. Binding to adipose, kidney, and lung can also be estimated with rat liver fu with scaling factors. This study suggests that a single tissue of a single species (e.g., rat liver) is a good predictor for fu of other tissues of various species with or without scaling factors. Molecular size, lipophilicity, pKa, and topological polar surface area are important physiochemical properties influencing tissue fu.

The design and performance of the exubera pulmonary insulin delivery system.

The Exubera system (Pfizer, New York, NY/Nektar Therapeutics, San Carlos, CA) is an integration of five major new technologies: protein formulation, powder processing, powder filling, drug packaging, and delivery device. The product provides a simple interface, where the patient interacts only with the delivery device and powder packaging. These components were designed together to assure repeatable dosing when used by a wide range of patients under real-world life-style and handling conditions. The device design is purely mechanical, using patient-generated compressed air as the energy source. Upon actuation, a sonic discharge of air through the novel release unit reproducibly extracts, de-agglomerates, and disperses the inhalation powder into a respirable aerosol. A clear holding chamber allows for patient feedback via dose visualization and separates aerosol cloud generation from the inspiratory effort. The Exubera product was tested under a wide range of typical use conditions and potential misuse scenarios and following long-term usage in clinical trials. These comprehensive characterization programs demonstrated robust aerosol and mechanical performance, confirming the design intent of the inhaler. These studies provide assurance of consistent and reliable dose delivery in a real-world use of the product.