The following Insight is a featured article from WCG’s 2025 Trends & Insights Report. If you would like to read more insights from this report, please click here.

In precision medicine, particularly in oncology, artificial intelligence (AI) is transforming patient care through predictive biomarker matching, which enables personalized treatment approaches that surpass traditional one-size-fits-all methodologies. Biomarkers, which are signature molecules that reflect biological states, have long been used to guide treatment decisions by predicting disease progression, patient response, and potential therapeutic efficacy. Biomarker-informed therapies have demonstrated success, with treatment response rates increasing from 20% to approximately 42% when biomarkers are used, according to data from the Personalized Medicine Coalition. However, challenges in data integration and the complexities of disease heterogeneity limit the widespread clinical adoption of biomarker-driven approaches.  

AI, specifically machine learning (ML), is proving to be pivotal in addressing these challenges. Unlike traditional biomarker methods that focus on individual traits, AI enables researchers to interpret intricate patterns across thousands of biological data points, creating a more holistic understanding of disease biology. For example, sophisticated ML algorithms can integrate diverse datasets, including genomic information, proteomics, and clinical trial data, allowing clinicians to develop dynamic, personalized treatment strategies. This data harmonization provides a comprehensive view of patient biological profiles, enhancing the precision of treatment selection.  

In practice, AI aids in multiple key areas of biomarker matching: data integration and management, predictive modeling, and dynamic biomarker tracking. Integrating data from various sources, such as electronic health records (EHRs), specialty labs and genomic databases, is crucial for effective biomarker discovery. Predictive analytics then enable clinicians to identify patients most likely to benefit from specific therapies, minimizing the trial-and-error approach that can characterize traditional treatments. Moreover, as biomarkers can evolve over time, AI’s continuous tracking capabilities allow for real-time adjustments, ensuring ongoing treatment relevancy. 

However, as AI-driven biomarker matching advances, ethical considerations regarding patient data privacy and algorithmic accuracy and transparency remain essential. Promoting ethical standards and transparency in AI applications fosters trust and ensures that technology translates into meaningful patient benefits. As AI continues to redefine biomarker matching in 2025 and beyond, it holds the potential to revolutionize clinical trial success rates, improve patient outcomes, and ultimately reduce healthcare costs across therapeutic areas.  

Related Insights:

Ethics in Clinical Research

Ethical Review & AI in Clinical Trials

Podcasts

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During this webinar, we turned our focus to the challenges unique to our innovative colleagues in the emerging biopharma space. With smaller and focused-pipeline organizations making up over 50% of clinical trials activity pre-COVID-19, these sponsors represent the potential for enormous advances in development, but also shoulder the challenges of keeping projects moving in highly concentrated pipelines during this time.

Our expert speakers discuss:

• How the agile nature of emerging biopharma has uniquely enabled them to pivot quickly and map to new methodologies to sustain and manage ongoing trials during the pandemic
• How organizations with focused pipelines or single assets are facing development and commercial realities going forward

We’ll speak with leaders from emerging biopharma organizations with assets in different therapeutic areas and in various phases of development and commercialization; and about the evolving resources that address biopharma needs during this time.

The post Part 10: Unique Challenges and Opportunities for Emerging Biopharma Companies with Focused Pipelines appeared first on WCG.

Early phase CNS research is plagued by a higher than average failure rate and complicated by a lack of discrete endpoints. As science evolves, hope arises. Today, we are able to improve our decision-making by increasing the number of objective data points collected in early phase research.  

Demanding Innovation

As the understanding of the central nervous system increases, so does the success in identifying a number of biomarkers and genetic components associated with neurological and psychiatric diseases. In an effort to increase the probability of success for investigational compounds, it is becoming more prevalent to incorporate alternative methods of identifying biological targets in order to more effectively screen new drugs. The use of functional magnetic resonance imaging (fMRI) in schizophrenia is giving companies the ability to assess target engagement and provide insights into the biological processes associated with the symptoms of schizophrenia. In fact, many biopharmaceutical sponsors try to de-risk their research portfolio by adding more biomarker data to early phase trials. If biomarkers indicate target engagement and hint toward efficacy, then companies will likely continue development.

Because decision-making in early phase clinical research is so important, many biopharma sponsors invite third-party experts to advise them on endpoint selection, trial methodology and design, and trial implementation strategies. WCG MedAvante-ProPhase helps sponsors bridge the gap between scientific integrity and operational excellence of their CNS research. We bring 25 years of experience in CNS and trusted data on 95% of all industry-sponsored protocols. Our CNS expertise, coupled with the scope of our data-driven insights, enables us to partner with biopharmaceutical sponsors who want to ensure that they are in the best possible position to succeed.

Having worked with every major sponsor in the industry, including emerging biopharma companies, we base our recommendations on unsurpassed clinical and scientific expertise, deep operational knowledge, and access to the highest volume of CNS-specific trial data in the industry. We’ve seen what works, and more importantly, what doesn’t.

So, what’s the takeaway?

Success means demanding innovation, especially in early phase CNS trials. Our industry is slow to change; we all know this. But we keep doing the same thing over and over again, expecting a different outcome. That’s the definition of insanity.

4 Recurring Risks to Consider in Early Phase CNS Research:

1. Protocols are becoming more complex, and highly specialized. Many protocols now involve a genetic component, which introduces its own risks and necessitates certain considerations.
2. Sponsors don’t often pay enough attention to site selection in CNS, especially in early phase. Often, they fail to consider which sites (if any) can actually execute the desired level of complexity.
3. As opposed to late phase research, Phase I and II research is conducted in comparatively small populations. With smaller numbers, the quality of data becomes increasingly important.
4. Identifying the perfect patient is like finding a needle in a haystack. Virtual trials are the wave of the future. This brings clinical research to the patient and provides greater access to untapped patient populations.

Confident Decision-Making 

When biopharma sponsors bring WCG MedAvante-ProPhase in to support early phase research, we help them to distinguish the “must-haves” from the “nice-to-haves’” in a given protocol design. This is particularly important because having the right requirements means finding the right patients to meet the proper enrollment criteria.

Based upon previous conversations with our CNS Scientific Leadership Team, we know that Principle Investigators (PI’s) often struggle with patient enrollment, particularly in CNS trials. By choosing the right sites and providing them with the right resources, we help clients to achieve enrollment 33% faster than average. This sets up sponsors for success from the very beginning of the clinical trial process.

Just like how a patient can go to a doctor for a second opinion, sponsors look to us for confident decision-making, especially our emerging biopharma clients, for whom we are an integral part of their process. By helping sponsors to accelerate the discovery of new treatments and therapies, we’re giving hope to the millions of patients and their families who are living with CNS disorders.

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