The opportunities and challenges inherent in using protein biomarkers for new drug development

Difficulties diagnosing disease earlier, failure to demonstrate efficacy, questions about safety and the sheer cost of testing constantly threaten new therapeutic development. But greater understanding and more widespread use of protein biomarkers have the potential to improve that narrative.

A biomarker indicates a medical state that can be measured accurately and reproducibly from outside a patient’s body. Think of measuring a patient’s blood pressure to diagnose hypertension and predict heart disease, heart attack or stroke. During drug development, a biomarker is evidence of disease at the molecular level, and a protein biomarker demonstrates that a human body reacted to a therapy. Monitoring the concentration of such proteins is a powerful tool to follow the outcome of a disease and a drug’s efficacy.

Protein biomarkers can bring clarity to invisible illnesses, improve prediction capabilities and quell the spread of a disease before it starts. They can also streamline clinical trials by helping identify populations, monitor therapeutic response and document a drug’s side effects. A better understanding of the opportunities and inherent challenges in protein biomarkers can help set expectations for drug developers pursuing them for regulatory submissions, eventually increasing their drug approval rate.

The scope of biomarker use

Protein biomarkers exist in biological matrices like cerebrospinal fluid (CSF), blood, urine and tissue. Hundreds of clinical studies conducted each year depend on biomarker data to diagnose, predict and fight the most challenging diseases. For example, in vivo studies have been used since 2003 to dissect the molecular mechanisms of chronic kidney disease. Unbiased genomic and proteomic screening technologies identified new constituents in biological samples that led to faster treatment and earlier, more accurate detection.

Likewise, treating lung cancer depends on the histological variant of the tumor. Detecting it is impossible without knowing the nature and origin of malignant cells that release protein biomarkers into the blood. So, accurately identifying and treating the top cancer killer in humans comes down to running the proper assay. Similarly, new blood-based protein biomarkers are also helping diagnose and more accurately predict treatment responses for women with breast cancer.

Finally, scientists developed a versatile and ultrasensitive assay to detect and quantify trace amounts of protein biomarkers to diagnose Alzheimer’s disease. Using this assay, researchers need only an hour to detect the biomarkers in CSF, serum, saliva or urine.

Diagnosing cancer, kidney disease and Alzheimer’s are just three ways protein biomarkers create opportunities to improve clinical work and refine drug development. Further developing and qualifying protein biomarkers can provide hope for countless patients currently (and potentially) suffering from chronic illness.

In addition to their diagnostic uses, biomarkers are powerful tools when used to document the outcome of a treatment. During early phase clinical trials, the expression of several proteins including, but not limited to, lymphokines, soluble receptors and enzymes are monitored. The correlation between these proteins and the outcome of the disease is investigated. For a given therapeutic, pinpointing a marker whose expression correlates with the outcome of the disease allows physicians to personalize treatment for individual patients. Thus, the identification and the quantitation of suitable biomarkers is one of the most promising tools in personalized medicine.

The built-in challenges using protein biomarkers

Protein biomarkers have been used for decades to help develop new drug candidates and treat chronic conditions, but they are inherently challenging.

The human body contains around 20,000 different proteins, but only a few hundred of them are appropriate for drug development. Biomarkers can change health outcomes through improved diagnostic, prognostic or measurement strategies, but their effectiveness depends on the sequence of actions scientists employ and the test results they find. One reason for the seemingly disjointed advancement of biomarker work is the limited ownership and collaboration between those identifying, validating and qualifying protein biomarkers across the academic and industry fields.

“One of the problems with biomarkers is there’s really no one in charge of developing them,” says Dr. Janet Woodcock, director of the FDA’s Center for Drug Evaluation and Research (CDER). “The community is divided into the biomedical research community that does discovery, the pharmaceutical industry and related industries that do development of specific medical products, and then us, the regulators, who oversee this process and set standards.”

Woodcock says having no one tasked with developing new biomarkers leads to an abundance of caution. “Thousands [of biomarkers] are discovered, and papers are published about them, but … if there’s not enough information to make decisions on, we’re not going to bet people’s health on these,” she says.

Drug developers, academic institutions and other researchers will often identify biomarkers they want to use. Laboratory partners also can be instrumental in validating and qualifying these related assays used to identify and organize biomarker data to support regulatory submissions.

Above all, the main challenge of biomarkers is what is represented by the presence of endogamous protein. Since the calibration curve of the bioanalytical method is often made out of a recombinant protein, sometimes the endogenous (natural occurring) protein present in the matrix may not be easily or precisely quantified. This makes it particularly challenging to rigorously assess a disease or treatment-induced through biomarker modulation.

Protein biomarker validation versus qualification

One of the primary modes of recognizing new protein biomarkers is through regulatory approval. Submissions for Investigative New Drugs (IND), New Drug Applications (NDA) and Biologic License Applications (BLA) may include biomarker data. If the submission is approved, the biomarker gains acceptance in that specific drug development program. One of the problems with this pathway is that the confidential discussions between drug developers and the U.S. FDA are not subject to input from the greater scientific community. Thus, all the data and information resulting from the discovery and development of these biomarkers is locked in confidentiality.

An alternative pathway for discovering, developing and using new biomarkers is through qualification. CDER developed the biomarker qualification program to encourage academia, industry and government stakeholders to work together to develop and evaluate various biomarkers for their intended use. A “context of use” statement determines the best use category for biomarkers and describes its intended purpose. The primary advantage of qualifying biomarkers is that the resulting data is publicly available and can be used in multiple drug development programs.

Analytical and clinical validation are necessary to support the qualification of a biomarker, and both contribute to a biomarker’s context of use. Biomarkers have different endogenous levels among the biologic samples, and validation is the complex process of optimizing the assay procedures to meet the needed sensitivity for the drug development program. Validated methods can provide more precise and accurate data, which can then be included in clinical trials, or secondary endpoints. A fit-for-purpose method qualification could be used as exploratory biomarker sample testing.

An experienced laboratory testing partner can help interpret guidance on biomarkers and help developers choose the pathway that makes the most sense for their therapeutic.

Final thoughts on protein biomarkers

Discovering a suitable protein biomarker can be dizzying. Identifying new biomarkers with the requisite precision and accuracy can be like finding a unique needle among a stack of needles. Moreover, validating and qualifying biomarkers can be a years-long process fraught with frustration and failure. Still, a dedicated team with expertise can speed up this process by implementing robust procedures and ensuring ongoing communication with regulatory agencies.

Drug developers should be mindful of two key considerations as they traverse the protein biomarker pathway. First, it is critical to stockpile enough critical reagents to get you through the life of the development process. For example, developers should think holistically about their programs to ensure they have enough antibodies for the biomarkers they’re testing.

Second, developers should be sure to set up their own laboratory or work with a suitable testing partner that has the knowledge and experience to navigate the various test platforms and the regulatory hurdles they will encounter. Biomarker identification and development may require techniques like LC/MS/MS, flow cytometry, enzyme-linked immunoassay (ELISA), mesoscale discovery (MSD) or immunohistochemistry. Partnering with a laboratory with expertise in the most relevant platforms can streamline testing and further reduce development timelines.

During the discovery stage, a fit-for-purpose method may be sufficient to evaluate the modulation of a biomarker during a pharmacological treatment. Once the biomarker is identified, it can personalize medicine, make profound and impactful decisions about patient treatment, and improve the drug approval rate.

Xuesong Chen joined WuXi AppTec in 2020 as a technical director supporting client engagement and technical discussions for preclinical and clinical large molecule bioanalytical services.

Chen received his Ph.D. in Pharmacognosy from Peking Union Medical College’s Chinese Academy of Medical Sciences and did his post-doctoral work in Physiology at the University of Texas Southwestern Medical Center in Dallas.

Before joining WuXi AppTec, Chen worked in high-throughput screening for novel lead compounds using automation systems and led a successful team specializing in MD/MV for biologics pharmacokinetics, anti-drug antibodies (ADA) and biomarkers for regulated studies. He has more than a decade of hands-on experience with ligand binding assay (LBA) using different platforms for Large Molecule (LM), including MSD, ELISA, ELLA, HTRF, AlphaLISA and Quanterix Simoa. He also has experience in cell-based functional assays using confocal microscopy and tissue/cultures staining assays based on immunohistochemistry. In addition, Chen recently developed two successful companion diagnostic kits for two different clinical trials under Clinical Laboratory Improvement Amendments (CLIA) regulations.

Clara Brando received her Pharma Doctor and her Ph.D. in immunology/Immuno-pathology from the University of Turin (Italy) in 1990. She received post-doctoral training at the Laboratory of Immunology at the National Institute of Allergic and Infectious Disease (NIAID) at NIH from 1990-94. During this time, Brando was trained in Cellular immunology with emphasis on T cell response

Brando has served as a senior scientist at Temple University, Wistar Institute and The Walter Reed Institute for Research, working on autoimmunity, immunity to cancer, and vaccines to infectious agents. Brando’s research focuses on the generation of cell-based and ligand binding assays to assess the cellular and humoral immune response to vaccines and therapeutics. Brando has developed various novel flow-cytometry, Elispots and Elisa assays to investigate T and B cell response.