Poll Results: How AI Will Impact Clinical Intelligence

AI's contribution to biotech has been predominantly highlighted in scientific discovery and drug development. However, its pivotal role in commercial biopharma functions, especially in managing vast data and informing business decisions, remains under-emphasized. A recent STAT Trials Pulse poll conducted by AppliedXL in collaboration with STAT News, involved 63 biopharma professionals, of whom 67% are senior executives and 33% are managers. The poll inquired about the most significant areas where AI is expected to have an impact over the next five years, specifically in relation to business operations, clinical intelligence, and marketing.

Beyond mere hype, AI has multifaceted applications in both R&D and commercial operations. Empowered by AI, commercial teams can process and interpret data at unprecedented speeds, resulting in enriched data quality, improved portfolios, and ultimately, taking new drugs to market faster.

AI uncovers risk and hidden business opportunities: 

According to our poll, teams emphasize the potential of AI in tasks related to business operations and decision making. Traditionally, evaluating risk, extracting market trends, and strategizing for clinical trials have been cumbersome and costly tasks. Challenges like information gaps or delays in clinical registries led to inefficiencies in workflow. AI offers the opportunity to streamline data processing, detect patterns, and continuously check the reliability of data, augmenting existing analysis methods while improving productivity. 

Nearly 50 percent of the people surveyed believe that AI's most promising five year impact on business operations lies in its ability to proactively identify potential risks.

1. Clinical Strategy and Risk Management (47%): AI identifies potential risks well in advance, guiding teams in strategic decision-making and trial planning.
2. Data Analysis and Forecasting (32%): AI offers precise drug market predictions and patient demand forecasts, directing business teams on optimal resource allocation.
3. Identifying New Business Partnerships (21%): AI reveals untapped business partnerships, acquisitions, or investment areas not evident through traditional methods.

Using AI to stay ahead of the competition:

Survey respondents also recognized the anticipated benefits of AI in the realm of clinical and competitive intelligence. Faced with a staggering 7,000 clinical updates every day (as indicated by AppliedXL data), manual sorting and analysis becomes a daunting chore for commercial biopharma. And when they manage to finally locate pertinent information, it can be swiftly rendered outdated by a relentless tide of fresh new data. AI presents an opportunity to not only streamline this process but also to expedite business intelligence, while reducing the costs associated with in-depth competitive intelligence.

‍Over half of the respondents anticipate that in the next fiver years AI will be most influential in uncovering hidden competitor insights.

1. Market and Competitor Insights (56%): AI provides continuous monitoring of competitors, delivering immediate updates on their programs’ progress and challenges.
2. Predictive Clinical Intelligence (30%): AI helps anticipate future clinical trial disruptions and regulatory approval hurdles based on historical competitor data. 
3. Drug Pipeline Adaptation (24%): AI forecasts competitors' target therapeutic areas and identifies areas of unmet need, shaping pipeline strategies grounded in historical data.

AI amplifies personalization and patient-centric outreach: 

Our survey also explored AI's pivotal role in reshaping how the industry will approach marketing activities. Past efforts to understand nuanced patient journeys or to tailor marketing messages often faced logistical and data challenges. People who responded to our survey believe that the introduction of AI will allow for a more comprehensive understanding of patient behaviors, more accurate forecasting of evolving market nuances, and the fine-tuning of communication channels for higher engagement.

‍The majority of respondents believe that marketing personalization will be a key  area with the greatest potential for future impact.

1. Patient Messaging Personalization (52%): AI enables to tailor campaigns by optimizing for specific demographics, providing personalized experiences, and gaining a deeper understanding of patient journeys.
2. Drug Penetration Forecast (26%): AI forecasts commercial viability and market size based on current treatments and patient needs enables more precise biotech product strategies.
3. Drug Launch Optimization (22%): AI pinpointings the most effective marketing channels for their drug launches, ensuring efficient resource allocation.

AI built specifically for commercial biopharma teams 

At AppliedXL, we are leading the AI charge with STAT Trials Pulse, a clinical intelligence platform powered by a language model created for biotech and grounded in journalism. It is designed to reduce manual data processes across all areas of work from trial monitoring to competitor tracking to investment research. Some of the leading biotech and pharma companies are using STAT Trials Pulse’s AI capabilities to :

• Run comprehensive analyses in minutes: Our AI analyzes thousands of clinical data points, allowing biotech leaders to find easy-to-share insights without any manual input.
• Catch risks months in advance: AI automatically detects setbacks and alerts you far before they become public news.
• Access exclusive data: We track almost 100 specific clinical trial events that aren’t available anywhere else.
• Maintain data integrity: Our algorithms strictly adhere to high journalism standards, guaranteeing rapid insights without compromising on ethics.

Conclusion: AI as a lever for productivity

The biotech industry is still struggling with an overreliance on basic analysis tools, limited automation, and fragmented datasets, which contributes to knowledge loss over extended development cycles. With the shift from blockbuster drugs to precision medicine, commercial teams are tasked with evaluating more markets without additional resources, leading to overextension. Smaller biotechs, with fewer resources than their larger counterparts, struggle to understand their markets adequately. The slow adoption of new technologies is often attributed to the cumbersome nature of non-integrative tools rather than reluctance to embrace new tech. Leveraging AI to improve efficiency presents a significant opportunity to boost productivity and narrow the gap between emerging biotech ventures and established pharmaceutical giants. If you’re interested in seeing how STAT Trials Pulse works for you, sign up for a free trial or get in touch with a member of our team.

‍_{Note: This poll, conducted in September 2023 via HubSpot survey tool, collated responses from 63 professionals in the pharmaceutical and biotech sectors. Of these, 67% were senior executives and 33% were managers, with affiliations ranging from pharmaceutical giants to emerging biotech companies. To enhance clarity in our findings, some data areas were aggregated, ensuring a clearer representation of trends without sacrificing the depth and validity of insights.}