Conference Report: Analytical challenges in the qualification and validation of pharmacodynamic biomarkers

Applied Clinical Tandem Mass Spectrometry-Based Quantification Methods for Lipid-Derived Biomarkers, Steroids and Cannabinoids: Fit-for-Purpose Validation Methods

The emergence of metabolomics and quantification approaches is revealing new biomarkers applied to drug discovery. In this context, tandem mass spectrometry is the method of choice, requiring a specific validation process for preclinical and clinical applications. Research on the two classes of lipid mediators, steroids and cannabinoids, has revealed a potential interaction in cannabis addiction and metabolism-related disorders. Here we present the development of GC-MS/MS and LC-MS/MS methods for routine quantification of targeted steroids and cannabinoids, respectively. The methods were developed using an isotopic approach, including validation for linearity, selectivity, LLOQ determination, matrix effect, carryover, between- and within-run accuracy and precision, and stability tests to measure 11 steroids and seven cannabinoids in human plasma. These methods were satisfactory for most validity conditions, although not all met the acceptance criteria for all analytes. A comparison of calibration curves in biological and surrogate matrices and in methanol showed that the latter condition was more applicable for our quantification of endogenous compounds. In conclusion, the validation of our methods met the criteria for GLP-qualified rather than GLP-validated methods, which can be used for routine analytical studies for dedicated preclinical and clinical purposes, by combining appropriate system suitability testing, including quality controls in the biological matrix.

Dried Blood Spot Technique Applied in Therapeutic Drug Monitoring of Anticancer Drugs: a Review on Conversion Methods to Correlate Plasma and Dried Blood Spot Concentrations

BACKGROUND

Anticancer drugs are notoriously characterized by a low therapeutic index, the introduction of therapeutic drug monitoring (TDM) in oncologic clinical practice could therefore be fundamental to improve treatment efficacy. In this context, an attractive technique to overcome the conventional venous sampling limits and simplify TDM application is represented by dried blood spot (DBS). Despite the significant progress made in bioanalysis exploiting DBS, there is still the need to tackle some challenges that limit the application of this technology: one of the main issues is the comparison of drug concentrations obtained from DBS with those obtained from reference matrix (e.g., plasma). In fact, the use of DBS assays to estimate plasma concentrations is highly dependent on the chemical-physical characteristics of the measured analyte, in particular on how these properties determine the drug partition in whole blood.

METHODS

In the present review, we introduce a critical investigation of the DBS-to-plasma concentration conversion methods proposed in the last ten years and applied to quantitative bioanalysis of anticancer drugs in DBS matrix. To prove the concordance between DBS and plasma concentration, the results of statistical tests applied and the presence or absence of trends or biases were also considered.

Targeting for Success: Demonstrating Proof-of-Concept with Mechanistic Early Phase Clinical Pharmacology Studies for Disease-Modification in Neurodegenerative Disorders

The clinical failure rate for disease-modifying treatments (DMTs) that slow or stop disease progression has been nearly 100% for the major neurodegenerative disorders (NDDs), with many compounds failing in expensive and time-consuming phase 2 and 3 trials for lack of efficacy. Here, we critically review the use of pharmacological and mechanistic biomarkers in early phase clinical trials of DMTs in NDDs, and propose a roadmap for providing early proof-of-concept to increase R&D productivity in this field of high unmet medical need. A literature search was performed on published early phase clinical trials aimed at the evaluation of NDD DMT compounds using MESH terms in PubMed. Publications were selected that reported an early phase clinical trial with NDD DMT compounds between 2010 and November 2020. Attention was given to the reported use of pharmacodynamic (mechanistic and physiological response) biomarkers. A total of 121 early phase clinical trials were identified, of which 89 trials (74%) incorporated one or multiple pharmacodynamic biomarkers. However, only 65 trials (54%) used mechanistic (target occupancy or activation) biomarkers to demonstrate target engagement in humans. The most important categories of early phase mechanistic and response biomarkers are discussed and a roadmap for incorporation of a robust biomarker strategy for early phase NDD DMT clinical trials is proposed. As our understanding of NDDs is improving, there is a rise in potentially disease-modifying treatments being brought to the clinic. Further increasing the rational use of mechanistic biomarkers in early phase trials for these (targeted) therapies can increase R&D productivity with a quick win/fast fail approach in an area that has seen a nearly 100% failure rate to date.

Biomarker development for axial spondyloarthritis

The term axial spondyloarthritis (axSpA) encompasses a heterogeneous group of diseases that have variable presentations, extra-articular manifestations and clinical outcomes, and that will respond differently to treatments. The prototypical type of axSpA, ankylosing spondylitis, is thought to be caused by interaction between the genetically primed host immune system and gut microbiota. Currently used biomarkers such as HLA-B27 status, C-reactive protein and erythrocyte sedimentation rate have, at best, moderate diagnostic and predictive value. Improved biomarkers are needed for axSpA to assist with early diagnosis and to better predict treatment responses and long-term outcomes. Advances in a range of 'omics' technologies and statistical approaches, including genomics approaches (such as polygenic risk scores), microbiome profiling and, potentially, transcriptomic, proteomic and metabolomic profiling, are making it possible for more informative biomarker sets to be developed for use in such clinical applications. Future developments in this field will probably involve combinations of biomarkers that require novel statistical approaches to analyse and to produce easy to interpret metrics for clinical application. Large publicly available datasets from well-characterized case-cohort studies that use extensive biological sampling, particularly focusing on early disease and responses to medications, are required to establish successful biomarker discovery and validation programmes.

Flow cytometry: a flexible tool for biomarker research

Flow cytometry is increasingly recognized as an invaluable technology in biomarker research. Owing to its multiparametric nature it can provide highly detailed information on any single cell in a heterogeneous population. Its versatility means it can be conducted in both the preclinical and clinical setting, generating biomarker data that can drive decisions pertaining to dose selection in clinical trials, treatment options for cancer sufferers and even suitability of patients to receive transplants. Most tissue types can be utilized by the flow cytometrist, allowing the technology to be applied to many fields of research, yet consensus still needs to be reached on standardization, regulation and validation of multiparametric flow cytometry assays. In parallel, continual innovation in analysis software to manage the huge datasets that can be generated is also needed. Nevertheless, the flexibility of flow cytometry means that it remains at the forefront of both routine and exploratory biomarker studies.