Tech & AI LIVE London – Lisa Moneymaker AI in Healthcare

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Lisa Moneymaker, Saama discusses how AI advancements are transforming clinical trials, focusing on accelerating drug development & improving data accuracy

During her keynote at Tech & AI LIVE London (virtual), Lisa Moneymaker, Chief Technology Officer and Chief Product Officer at Sama, addressed how artificial intelligence (AI) and machine learning are revolutionising clinical trials. 

Moneymaker begins by explaining the traditional process of drug development, which involves multiple phases of clinical trials to determine the safety and effectiveness of new drugs. “Many drugs take decades to get to market,” she states, noting the long and complex journey most treatments undergo from initial research to final approval.

Moneymaker uses the rapid development of COVID-19 vaccines as an example of what is possible when significant resources and technology are combined to solve global challenges. 

“We moved from decades to a single year to get drugs to market,” she highlights, adding that Sama’s goal is to make such accelerated timelines more common by leveraging advanced technology.

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Using AI to analyse and manage vast data sets

Moneymaker explains that one of the key issues in clinical trials is the growing volume of data. This data explosion, seen across many industries, has increased the need for effective data processing and analysis. 

In clinical trials, data can range from traditional medical records to continuous monitoring data from wearables like smartwatches. The challenge is not just collecting this data, but making sense of it all in a way that informs decisions.

“We have to be able to aggregate and clean data to ensure accuracy,” Moneymaker emphasises. AI can play a crucial role here, as it can help identify missing information, detect discrepancies, and analyse complex data sets faster than human researchers alone. 

Sama has incorporated machine learning models into its products to help clinical trial professionals track and correct data in real-time, preventing errors from delaying trials.

Lisa Moneymaker, Chief Technology Officer and Chief Product Officer at Sama

AI’s role in patient monitoring and predictive analysis

Moneymaker highlights how AI can predict patient behaviour and flag potential risks. For example, Sama’s algorithms can analyse historical and ongoing trial data to identify patients who are at risk of early withdrawal or adverse events based on their lab results and response patterns. 

By surfacing these risks to clinicians in real-time, AI helps healthcare professionals make informed adjustments to the trial, improving both patient safety and data quality.

She describes how Sama’s AI-powered “Smart Suggestions” feature works, providing clinicians with predictions and confidence scores based on patient data. 

“We’re moving people from a prediction to an action that they can take,” Moneymaker explains. In practice, this could mean alerting a clinician to four patients who are at high risk of leaving a trial, allowing them to intervene proactively.

Lisa Moneymaker, Chief Technology Officer and Chief Product Officer at Saama

Ensuring data quality and compliance

One of the most significant challenges in clinical trials is ensuring that data is accurate and complete. Moneymaker emphasises that AI can assist with this by identifying duplicate entries, missing data points, or inconsistencies between different sources. 

Moneymaker also discusses the regulatory environment in healthcare and the cautious approach taken towards fully autonomous AI decision-making. While AI can support clinicians with insights and predictions, human oversight remains essential. 

“AI supports decision-making, but the final call is always made by a human,” she explains, noting that Saama stays within regulated boundaries by ensuring that AI remains a tool for augmenting human expertise rather than replacing it.

Ensuring data quality and compliance

One of the most significant challenges in clinical trials is ensuring that data is accurate and complete. Moneymaker emphasises that AI can assist with this by identifying duplicate entries, missing data points, or inconsistencies between different sources. 

Moneymaker also discusses the regulatory environment in healthcare and the cautious approach taken towards fully autonomous AI decision-making. While AI can support clinicians with insights and predictions, human oversight remains essential. 

“AI supports decision-making, but the final call is always made by a human,” she explains, noting that Sama stays within regulated boundaries by ensuring that AI remains a tool for augmenting human expertise rather than replacing it.

Lisa Moneymaker, Chief Technology Officer and Chief Product Officer at Saama

Looking ahead: Trends and advancements in AI for healthcare

When asked about future trends, Moneymaker expresses optimism about the rapid advancements in generative AI and large language models (LLMs) tailored for medical applications. 

“We’re seeing breakthroughs in refining medical-specific models to interact more natively with data,” she notes. These advancements allow AI to perform more exploratory work with less pre-programming, increasing the range of problems that can be solved.

Moneymaker also highlights the differences in applying AI to various medical fields. For example, oncology has vast amounts of historical data, which makes it easier to develop predictive models.

In contrast, rare diseases with limited patient data present more complex challenges. She encourages a focus on finding AI solutions for areas with scarce data, recognising the unique opportunities and difficulties that lie ahead.

Lisa Moneymaker’s keynote provided a comprehensive look at how AI is reshaping clinical trials and accelerating drug development. By improving data quality, predicting patient risks, and supporting decision-making, AI has the potential to bring life-saving treatments to market faster. Through continued advancements and collaboration, Moneymaker believes the industry can achieve significant breakthroughs in the coming years.

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