Bioanalytical services are among the most frequently outsourced Chemistry, Manufacturing, and Control (CMC) activities for pharmaceutical and biopharmaceutical companies. Bioanalytical services play an essential part in therapeutic molecule development while meeting regulatory expectations to obtain Investigational New Drug (IND) approval.
Kernstock and Bose offer their insights on how to plan and design bioanalytical studies effectively.
Bioanalytical Method Development
Pharmaceutical development can be an intensive and time-consuming process, and bioanalytical methods are integral to its success at every step. Therefore, it’s critical that bioanalytical methods used throughout are properly validated at each step and when moving them between laboratories or companies. To ensure reliable results that can be trusted upon, follow FDA guidance regarding validation as well as guidelines issued by International Council for Harmonization for bioanalytical method validation processes.
Establishing an analytical method requires first creating a method plan, including selecting appropriate reference standards and establishing its performance characteristics. Once complete, an experimental design can then be used to develop and optimize an analytical procedure; including optimizing parameters like column selection, mobile phase composition, detector conditions and gradient conditions in order to reach peak method performance.
Once a robust analytical method has been devised, the next step in its validation should be evaluated in biological samples to demonstrate that it can accurately and reliably measure analytes of interest in samples. There are three distinct forms of validation, including full validation, partial validation and cross-validation that must be undertaken prior to further use of bioanalytical methods.
Validating a bioanalytical method requires using identical experimental conditions and parameters, then comparing results against an established reference standard. Evaluation should take into account several parameters, including accuracy, precision, specificity, linearity range lower limit of quantification (LLOQ) ruggedness etc.
Partial validation compares an analytical technique with a pre-validated method in a different sample type or laboratory instrument or software; such as plasma to urine samples or different laboratory, instrument, or software environments. Cross validation involves comparing results from two bioanalytical methods in full or partial validation settings and can involve comparing LC-MS/MS or ELISA results as part of this comparison process.
Bioanalytical Method Validation
Bioanalytical laboratories service play an integral part in drug development by accurately measuring drug effects and efficacy through bioanalytical analyses conducted on biological samples such as saliva, urine or plasma samples from subjects. To accomplish these goals, accurate yet robust analytical methods must be created – this is where skilled scientists in bioanalytical laboratories come into play.
Any bioanalytical method must first be thoroughly validated to ensure accurate and reliable results, before it can be put into routine analysis. Validation requires showing that an assay can accurately measure known concentrations of an analyte or its metabolites from a given species in their biological matrix through replicate sets of reference standards, calibration standards, and quality control samples; then its accuracy and precision can be determined based on these analyses.
Full method validation should also include an evaluation of the stability of analyte in its sample matrix under intended storage conditions, typically through performing freeze-thaw cycles on triplicate samples and then comparing their results against anticipated values to determine whether or not this method can be routinely applied.
Bioanalytical labs must validate not only their analytical method but also ensure all samples are collected, stored, and shipped accurately – failure to do so could significantly delay clinical research as well as compromise sample integrity and thus data accuracy.
Finalize, a bioanalytical laboratory should also generate reports on their analytical results. These reports should contain tables listing all samples analysed with identification numbers, the results for each sample analysed, any deviations from method protocol as well as possible reasons for these deviations, calibration curve data and equations used for backcalculation should also be included; further documentation may be necessary depending on project specifications or individual studies.
Bioanalytical Data Analysis
As part of the drug development process, accurate and reliable bioanalytical data analysis is vital. This essential element plays a significant role in both drug discovery and nonclinical development phases as well as clinical trials; without reliable bioanalytical methods it would be difficult to evaluate an investigational drug candidate accurately in terms of its PK, PD, and toxicology profiles.
Bioanalytical analysis involves measuring concentrations of analytes–drugs and their metabolites–in biological samples like blood, urine, saliva or tissue extracts using analytical chemistry methods with high precision such as liquid chromatography mass spectrometry (LC-MS-MS) for small molecules or metabolites analysis or enzyme-linked immunosorbent assays (ELISA) for macromolecule and protein analyses.
When investigating a new drug, identification and quantification are the cornerstones of bioanalytical analysis. Precise analysis allows for accurate PK, PD and toxicology studies that provide timely decision making – which is particularly pertinent during preclinical drug development and when filing an Investigational New Drug Application (IND) with FDA or creating an NDA/IND combination application for an existing pharmaceutical product.
As bioanalytical processes move through each stage of drug development, it’s vital to validate assay methods according to ICH and FDA guidance for industry. Validation provides confidence in data generated for PK/TK studies as well as preparation for GLP clinical study filings.
Bring new drugs to market is no simple undertaking, requiring reliable assays and methodologies in all stages of bioanalytical testing. Automation streamlines many of these processes to enhance assay reliability, timeliness and quality analytics–helping ensure your drug’s PK/TK results are accurate, reproducible and compliant.
As per industry guidance from ICH and FDA, it’s also crucial to understand the different levels of validation required for bioanalytical assays. Assays used to support clinical trial submissions such as an IND or NDA should have full validation performed, while exploratory studies may need lower levels.
Bioanalytical Report Writing
As the starting point in drug development, bioanalytical testing plays an integral part of every stage of drug DMPK and clinical studies. Unfortunately, however, the pharmaceutical industry can struggle to ensure these tests are conducted efficiently due to challenges like finding suitable methods or managing complex biological matrices with millions of compounds that impede precise and accurate concentration evaluation.
To avoid such complications, it is important to understand the bioanalytical process and any steps required for validating reports. Proper documentation allows results to be recreated even in cases of failure; to ensure this, make sure you clearly state your purpose for performing an analysis, use specific terms to describe each step in its completion, and include any deviations from a standard set of results in your document.
An effective bioanalytical report should include a well-detailed validation plan outlining experiments and acceptance criteria, along with any regulatory work. Furthermore, any bioanalytical reports performed under regulation should include a quality statement from their quality assurance unit for such work.
Finaly, an ideal bioanalytical report should include all raw data used for the assay as well as a comprehensive listing of chromatograms from each run. Furthermore, setting an arbitrary minimum number (e.g. 5-20% of each sample’s initial 5 or 20% chromatograms) that will be included will help prevent cherry picking of data and ensure only relevant information is reported on.
Bioanalytical tests are integral components of drug development; yet many pharmaceutical companies struggle with setting up infrastructure and procedures necessary for these assessments. By carefully selecting an analytical method for each sample analysis, bioanalytical companies can reduce errors while providing meaningful data that support project goals.
