Development of an effective cleaning technique and ancillary analytical method for estimation of residues of selected kinase inhibitors from stainless steel and glass surfaces by swab sampling.

Importance of cleaning validation in the pharmaceutical industry cannot be overstated. It is essential for preventing cross-contamination, ensuring product quality & safety, and upholding regulatory standards. The present study involved development of an effective cleaning method for five selected kinase inhibitors binimetinib (BMT), selumetinib (SMT), brigatinib (BGT), capmatinib (CPT), and baricitinib (BRT). For checking the effectiveness of the developed cleaning technique, a sensitive and specific RP-HPLC based analytical method employing a diode array detector has been established to quantitate drug residue on glass and stainless steel surfaces. A reproducible swab sampling protocol utilizing TX714A Alpha swabs wetted with an extracting solvent has been developed to collect representative samples from both surfaces. Chromatographic separation of selected kinase inhibitors was achieved in gradient mode using an Agilent Zorbax eclipsed C18 column with acetonitrile and 10 mM ammonium formate as the mobile phase. The analytes were chromatographically separated in a 12 min run time. The mean swab recovery for each drug from glass and stainless steel surfaces exceeded 90%. Cleaning with IPA (70%) and acetone (70%) effectively removed residues for all five drugs. A solution comprising 10 mM SDS with 20% IPA demonstrated good efficacy in cleaning residues of BGT, BRT, and CPT, but exhibited lower efficacy for SMT and BMT.

Progressive tools and critical strategies for development of best fit PBPK model aiming better in vitro-in vivo correlation.

Nowadays, conducting discriminative dissolution experiments employing physiologically based pharmacokinetic modeling (PBPK) or physiologically based biopharmaceutical modeling (PBBM) is gaining significant importance in quantitatively predicting oral absorption of drugs. Mechanistic understanding of each process involved in drug absorption and its impact on the performance greatly facilitates designing a formulation with high confidence. Unfortunately, the biggest challenge scientists are facing in current days is the lack of standardized protocol for integrating dissolution experiment data during PBPK modeling. However, in vitro-in vivo drug release interrelation can be improved with the consideration and development of appropriate biorelevant dissolution media that closely mimic physiological conditions. Multiple reported dissolution models have described nature and functionality of different regions of the gastrointestinal tract (GI) to more accurately design discriminative dissolution media. Dissolution experiment data can be integrated either mechanistically or without a mechanism depending primarily on the formulation type, biopharmaceutics classification system (BCS) class and particle size of the drug substance. All such parameters are required to be considered for selecting the appropriate functions during PBPK modeling to produce a best fit model. The primary focus of this review is to critically discuss various progressive dissolution models and tools, existing challenges and approaches for establishing best fit PBPK model aiming better in vitro-in vivo correlation (IVIVC). Strategies for proper selection of dissolution models as an input function in PBPK/PBBM modeling have also been critically discussed. Logical and scientific pathway for selection of different type of functions and integration events in the commercially available in silico software has been described through case studies.

Refinement of safety and efficacy of anti-cancer chemotherapeutics by tailoring their site-specific intracellular bioavailability through transporter modulation.

Low intracellular bioavailability, off-site toxicities, and multi drug resistance (MDR) are the major constraints involved in cancer chemotherapy. Many anticancer molecules fail to become a good lead in drug discovery because of their poor site-specific bioavailability. Concentration of a molecule at target sites is largely varied because of the wavering expression of transporters. Recent anticancer drug discovery strategies are paying high attention to enhance target site bioavailability by modulating drug transporters. The level of genetic expression of transporters is an important determinant to understand their ability to facilitate drug transport across the cellular membrane. Solid carrier (SLC) transporters are the major influx transporters involved in the transportation of most anti-cancer drugs. In contrast, ATP-binding cassette (ABC) superfamily is the most studied class of efflux transporters concerning cancer and is significantly involved in efflux of chemotherapeutics resulting in MDR. Balancing SLC and ABC transporters is essential to avoid therapeutic failure and minimize MDR in chemotherapy. Unfortunately, comprehensive literature on the possible approaches of tailoring site-specific bioavailability of anticancer drugs through transporter modulation is not available till date. This review critically discussed the role of different specific transporter proteins in deciding the intracellular bioavailability of anticancer molecules. Different strategies for reversal of MDR in chemotherapy by incorporation of chemosensitizers have been proposed in this review. Targeted strategies for administration of the chemotherapeutics to the intracellular site of action through clinically relevant transporters employing newer nanotechnology-based formulation platforms have been explained. The discussion embedded in this review is timely considering the current need of addressing the ambiguity observed in pharmacokinetic and clinical outcomes of the chemotherapeutics in anti-cancer treatment regimens.

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics.

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

Cytochrome P450 enzymes: a review on drug metabolizing enzyme inhibition studies in drug discovery and development.

Assessment of drug candidate's potential to inhibit cytochrome P450 (CYP) enzymes remains crucial in pharmaceutical drug discovery and development. Both direct and time-dependent inhibition of drug metabolizing CYP enzymes by the concomitant administered drug is the leading cause of drug-drug interactions (DDIs), resulting in the increased toxicity of the victim drug. In this context, pharmaceutical companies have grown increasingly diligent in limiting CYP inhibition liabilities of drug candidates in the early stages and examining risk assessments throughout the drug development process. This review discusses different strategies and decision-making processes for assessing the drug-drug interaction risks by enzyme inhibition and lays particular emphasis on in vitro study designs and interpretation of CYP inhibition data in a stage-appropriate context.