1 week Ago By Kathy Vuksanaj
Interest in biomarkers has exploded in recent years, driven by improvements in data collection and analysis, burgeoning interest in personalized medicine, and efforts to increase the success rate for drug development. Although biomarkers were historically used as diagnostic tools, today they span every aspect of healthcare, such as predicting disease risk, monitoring disease progression, and assessing treatment response. They are also used by drug developers to streamline a path into the clinic.
In the drug discovery process, biomarkers can facilitate the investigation of a disease’s or drug’s mechanism of action, the selection of a specific patient population, and the assessment of each patient’s response. Overall, they make clinical trials more precise and cost-effective while reducing side effects, leading to better patient outcomes and faster regulatory approvals. But it’s not all smooth sailing.
The processes of finding, validating, and analyzing biomarkers come with many challenges that drug development companies are still working to overcome. Biomarkers are often categorized by their intended uses. For example, pharmacodynamic biomarkers, which measure the effects of a drug on a target, include phosphoproteins, which serve as key biomarkers in cancer signaling pathways.
However, if there isn’t a well-established biomarker for a particular role, or if the current biomarkers are insufficient to perform a certain task, companies must look for a new one. According to Sygnature Discovery, which specializes in the identification and validation of pharmacodynamic biomarkers, the discovery process depends on the collection and analysis of data, activities that can be enhanced by the use of omics and bioinformatics technologies. But the discovery process still poses many challenges.
“Challenges in biomarker discovery include biological variability, sample heterogeneity, and the need for rigorous validation,” says John Woolley, PhD, head of biomarkers, Sygnature Discovery. “Overcoming these challenges requires robust study design, accurate preclinical models, advanced analytical techniques, and deep data analysis. Collaborative efforts between academia, industry, and regulatory bodies can also facilitate the standardization and validation of new biomarkers from preclinical discovery to clinical approval.
” Woolley’s remarks could be taken as an illustration of one of Sygnature’s achievements. While working with a drug discovery and development company, Sygnature participated in the development of a novel patented biomarker assay for glucocorticoid receptor antagonism (Bali et al. 2016; 101: 4305–4312).
Currently, the assay is being used in Phase III trials in which Relacorilant, a glucocorticoid receptor antagonist, is being evaluated as a treatment for Cushing’s syndrome. To select the correct biomarker, many factors need to be considered, including the biomarker’s intended use and the mechanisms of the disease and treatment in question. “In principle, each therapy and indication requires its own biomarker in the sense that it must be clinically proven to work for the specific treatment and indication combination,” says Stefan Kostense, PhD, director of discovery sciences, Charles River Laboratories.
“If there is no surrogate biomarker available, drug developers should spend effort in exploring new biomarkers.” The biomarker discovery process begins by identifying potential biomarkers. This can be done by mapping out the target’s pathway or by using higher-resolution omics technologies, such as proteomics or epigenomics technologies.
Suspected biomarkers are then tested to determine which are associated with a response to the treatment. While this process may sound straightforward, there are some hurdles to overcome, such as cost. “The investments required to discover new biomarkers are extensive,” Kostense warns.
“We find that clients are hesitant to spend money to explore biomarkers, especially in early discovery, when the viability of their new drug candidate is unclear. Ultimately, however, investing in biomarkers to support drug development will pay out in the substantial increase in the probability of later success.” Another challenge is the requirement for an in-depth scientific understanding of the disease pathway.
Fortunately, exploring new molecules in the biomarker discovery process can reveal connections with disease or drug interactions, as can utilizing omics technologies. Charles River has expertise in disease biology across all therapeutic areas, as well as in state-of-the-art omics technologies, resulting in an excellent track record in delivering preclinical biomarker candidates at a rate nearly double the industry average. Omics technologies have been advancing rapidly, and there are some improvements in development that could greatly aid the biomarker discovery process.
Mission Bio’s multiomics platform, Tapestri, can analyze DNA and protein changes in a single sequencing run and provide single-cell genotype and phenotype data on thousands of cells. Unlike bulk next-generation sequencing, single-cell assays can colocalize events, such as copy number variations, point mutations, and protein expression, and give a precise clonal hierarchy. However, requiring the isolation of a single cell for analysis limits the types of diseases the platform can be used to study.
The most straightforward applications are for assessing blood cancers. These applications involve samples that are already single-cell suspensions. The Tapestri platform is about 10 years old and well established as a valuable research tool.
For example, in a study published last June, Stanford researchers used the Tapestri platform to investigate a case of secondary T-cell lymphoma following CAR T-cell therapy (Hamilton et al. . 2024; 390: 2047–2060).
Mission Bio is currently working on technical enhancements, such as ways to be responsive to solid tumors and measure additional features in cells, to expand its current application portfolio. The company is also building data sets to support more regulatory approvals to get Tapestri into the clinic. “We’re in the early stages of generating clinically relevant data,” says Todd Druley, MD, PhD, chief medical officer, Mission Bio, “and we’re trying to make the statistical argument that certain patients probably will do better if we bring these more advanced diagnostic tools to bear.
” Once a candidate biomarker is identified, it needs to be validated to ensure that it’s the right biomarker for the job. A common approach is to use diseased and nondiseased human tissues, to determine the biomarker’s relevance to the disease and to verify that the biomarker is expressed in the patient population, and to what extent. The goal is to establish the biomarker’s reliability, specificity, and accuracy, so it’s essential that the model closely represents the ultimate clinical use.
To support these efforts, Precision for Medicine has an inventory of 3.5 million formalin-fixed paraffin-embedded tissues together with a network of over 100 hospitals for prospective tissue collections from diseased and healthy patients. The assays selected to evaluate the biomarker in a clinical setting must also undergo a validation process to ensure they are robust and reliable and that they will provide accurate and valuable data.
Because good assays require good samples, the logistics and management of biosamples during clinical trials needs to be considered when selecting biomarker assays. For global studies, assays that require a fresh sample to be processed within 24 hours of collection can pose a challenge. To address this limitation, Precision for Medicine has its own global laboratory network, supplemented with partner processing laboratories around the world.
The company also provides platforms that allow for longer collection times. “If you’re not going to be able to use a flow assay because you can’t get your blood to a laboratory to get it processed within an acceptable window, we’ve got a proprietary epigenetic platform for immunophenotyping that is DNA-based,” says Amanda Woodrooffe, PhD, senior vice president and general manager, UK Labs, Precision for Medicine. “Data can be generated from a dried blood spot.
” Establishing the best biomarker and assay for a particular study helps to eliminate some of the challenges in bioanalysis. In fact, for Emery Pharma, which provides a range of bioanalytical services, this process begins with developing and validating analytical techniques, followed by the proper collection, storage, handling, and preparation of samples, and finally the analysis, data interpretation, and reporting. “This methodical approach ensures that biomarker measurements are robust and reliable,” says Prajita Pandey, PhD, assistant director of chemistry, Emery Pharma.
“It reinforces their critical role in advancing personalized medicine and improving patient care.” By meticulously managing critical variables, Emery Pharma does all it can to ensure the success of the bioanalysis. But there are some variables beyond its control.
For instance, as with biomarker discovery, bioanalysis is limited by the biological variability between patients and the disease’s complexity. In addition, detecting biomarkers accurately in complex biological tissues is technically challenging, while deriving meaningful insights from data analysis requires sophisticated statistical methods. Addressing these limitations requires scientists across disciplines to collaborate to advance the technologies and analytical methods they use.
At Emery Pharma, scientists avail themselves of several methods, including ligand-binding assays (such as ELISA) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), liquid chromatography–high-resolution MS, and hybrid immunoaffinity–LC-MS/MS assays. “Biomarkers are pivotal in every stage of drug development due to their multifaceted utility,” Pandey remarks. “Overall, biomarkers streamline drug development by improving decision making, optimizing trial designs, and facilitating the development of personalized medicine approaches that ultimately improve patient outcomes.
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