Technology Is Revolutionizing Evidence Synthesis in Biopharmaceuticals

The biopharmaceutical industry has made key advances in biotechnology and personalized medicine, with increasing emphasis on omics data analytics. In the oncology segment, recent breakthroughs in cell and gene therapy – such as chimeric antigen receptor (CAR)-T – have significantly improved clinical outcomes via a targeted approach to immune-oncology. However, these advances demand continuous updates regarding safety and efficacy prior to market access.

Extensive literature reviews are required to enable valuable evidence synthesis. These reviews not only enable oncology-focused biopharma companies to stay abreast of the latest research outcomes in the oncology field, but also help identify emerging trends to inform future oncology pipelines. This principle also applies to all other therapeutic areas. A meticulously performed literature review is required to synthesize the clinical evidence needed to guide research and development efforts, inform clinical trial design, and ensure regulatory compliance.

Recognizing the importance of this process, global biopharmaceutical companies have invested substantial resources into building advanced evidence synthesis capabilities. In the field of oncology, for instance, these efforts aim to address tailored clinical and scientific queries about specific cancer types without compromising patient-centricity. Effective evidence synthesis involves systematically reviewing, integrating, and interpreting research findings from multiple studies to draw comprehensive conclusions.

However, it is next to impossible for any biopharmaceutical company to build these in‑house capabilities. Curating actionable insights demands sifting through a plethora of literature, making manual efforts an extremely arduous task. Additionally, stringent regulatory scrutiny and intense competition necessitates out-of-the-box solutions: solutions that enable efficient, accurate, and swift curation of vast amounts of scientific literature. Consequently, there has been an exponential rise of digital solutions that include or do not include artificial intelligence (AI)/machine language (ML) in the evidence synthesis (ES) space.

Here, we will explore the areas where biopharma can benefit from high-impact evidence synthesis technologies, with a particular emphasis on the oncology field.

Evidence Synthesis: Applications

The process of evidence synthesis is vital for several reasons, each of which fosters efficacy, safety, and innovation in the biopharmaceutical industry.

1. Informing Clinical and Regulatory Decision-Making

Regulatory bodies such as the Food and Drug Administration (FDA) require extensive evidence to inform the risk-benefit profile of any experimental new drug or biopharmaceutical product. A robust compilation of available clinical literature on ongoing and completed clinical trials is essential for producing regulatory dossiers.  

Additionally, evidence synthesis findings help the research community design more effective clinical trials, as they possess a better understanding of the efficacy and safety profile of their biopharmaceutical product.  

2. Enhancing Drug Development Efficiency

The identification of research gaps from effective evidence synthesis helps streamline the research process, saving time and resources. It also helps ensure that no duplicate studies are conducted and facilitates the addition of new knowledge to an existing base. It identifies areas with unmet clinical needs faster and helps prioritize research directions, improving the likelihood of study success and accelerating biopharmaceutical product development.

3. Supporting Personalized Medicine

By integrating data from diverse studies, researchers can identify patient subgroups that respond differently to treatments, leading to more tailored and effective therapies. This includes “smart” identification of biomarkers or the application of stratified medicine concepts.

4. Facilitating Evidence-Based Practice

Synthesized evidence forms the basis for the creation of or updates to clinical guidelines and best practices. These guidelines help healthcare providers make informed decisions about standardized patient care, ensuring treatments are based on the best available evidence across a wide range of environments.

5. Driving Innovation

The biopharmaceutical industry relies on evidence synthesis as a catalyst for innovation.By identifying novel therapeutic targets from synthesized evidence, biopharmaceutical companies can gain a commercial advantage and devise innovative go-to-market strategies using honed competitive intelligence.

Evidence Synthesis: Automation Challenges

While deploying automation in evidence synthesis workflows, biopharmaceutical companies face several crucial challenges. However, human-in-the-loop (HITL) design comes to the proverbial rescue, overcoming most of these challenges by balancing smart technology with expert human oversight.

Challenge: Data Quality due to Variable Data and Lack of Standardization Across Studies

Challenge: Complexity and Context

Challenge: Integration with Existing Workflows

Challenge: Regulatory Compliance

Challenge: Ethical Considerations

Challenge: Adaptability and Flexibility

Evidence Synthesis: Impact ofAutomation

When considering evidence synthesis, automated technology offers tangible impact in three key ways:

Speed: Advanced tools significantly reduce the time required to complete evidence synthesis. Tasks that take months now take weeks or even days. In oncology, for instance, complex, time-consuming interpretations of survival analysis curves or partitioned survival models can be simplified with the use of appropriate technology.  

Accuracy: Automation minimizes human error, ensuring more reliable and reproducible results. For example, manually sorting relevant articles based on title and abstract can miss important key words, leading to human error. A smart algorithm can auto-sort articles, although it is worth noting that the accuracy of such an algorithm depends on its training dataset, validation methods, and scientific acumen of the user.

Scalability: These tools can handle large-scale analyses using extensive datasets that are simply impractical to perform manually.  

Conclusion: The Future of Evidence Synthesis is Human-in-the-Loop

The current evidence synthesis landscape in biopharmaceuticals clearly demonstrates the power of a human-in-the-loop approach. By harnessing the strengths of both human expertise and advanced automation, HITL ensures the accuracy, contextual understanding, and regulatory compliance that are critical for success. This balanced methodology not only streamlines the evidence synthesis process, but also empowers researchers to focus on innovation and ultimately improve patient outcomes.

Biopharmaceutical companies that embrace HITL stand to gain a significant competitive advantage.Integrating a HITL solution like Genpro Research's MAIA Evidence module helps medical affairs, medical writing, and pharmacovigilance professionals:

At Genpro, we understand the unique challenges and opportunities facing biopharma companies today. That's why we've developed MAIA Evidence, a state-of-the-art solution that goes beyond automation. MAIA empowers your expert analysts and writers with optimal control, ensuring the perfect balance between speed, accuracy, and robust reporting capabilities. This allows you to stay ahead of the innovation curve and dedicate crucial resources to drug development and post-launch activities.

Click here to learn more about MAIA Evidence.

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