mexec speaks with Michelle Gallaher, digital health entrepreneur and CEO of Opyl, on the role of artificial intelligence in healthcare.
Tell us a bit about what you do.
Opyl provides access to AI-assisted decision support and clinical trial recruitment technologies for the life sciences and health industries. Our proprietary digital platforms aim to improve decision-making particularly around improving efficiencies in clinical trial recruitment and protocol design as well as provide insight into patients and healthcare providers through social media.
We currently have 3 platforms:
– Opin – a clinical trial recruitment platform which matches patients to clinical trials anywhere in the world
– Trial Key – uses big data and predictive analytics to model trial protocols, assigning a probability of success and providing insight into how to adapt trial protocols to improve outcomes
– Social Media Insights – a listening tool that gathers data and provides evidence-based insights from healthcare professionals, patients and carers who share their experience and opinions publicly to social media.
How is AI-assisted technology changing the health and life sciences industry?
The role of AI is really to free up people from those mundane “middle-office” tasks, enabling them to focus on human-centred, high value activities. AI is about speed, accuracy, and accessibility as it can identify patterns in data that humans can’t, or at least at speed. Good quality AI requires good quality data, plus quality decisions and training from humans to ensure reliable results. You can’t have one without the other.
AI is changing the industry in terms of early diagnosis, drug discovery, treatment planning and care efficiencies, decision support and augmentation, rehabilitation and therapeutic optimisation and personalisation. Some therapeutic and discovery areas are more aligned with emerging AI technologies than others, but every area of the healthcare and lifesciences sector is now coming into contact with AI technologies.
I’ve seen AI used in various ways across the industry. If you take drug development for example, the consequence of a delayed a clinical trial because of a poorly designed protocol or slow recruitment could mean significant erosion of the value of the product through lost revenue, reduced patent life, competitor advantage and most importantly the inability of a patient to access therapies or diagnostics.
With 86% of clinical trials failing to recruit on time or on budget, AI has a valuable role to play in improving access for patients, as well as trial efficiencies and cost and risk reduction.
Can you share an example of where your Insights technology has been used?
One that immediately comes to mind is a company that was developing a product for a neurodegenerative disorder. They wanted to identify key opinion leaders in the digital space and understand what these KOLs were talking about publicly in terms of treatment options, use of a competitor product, and to understand their influence relationships with each other.
Through our social insights offering, we were able to gather business intelligence to identify digital KOLs (DOLs), map influence across their global networks, identify the specific language and terms they were using (which was unusual) and at the same time uncover unmet clinical needs and market messaging and adoption opportunities.
How do you then filter these digital conversations to ensure the quality of the data being captured?
We use natural language processing and machine learning, types of AI, to look at patterns, clusters and groups within text, filtering the noise from the value. We can also stack and analyse data from other sources with social data, to validate and expand information. The life sciences industry is notorious for using jargon but the solution that we have is industry-specific and able to put these words into context. For example, the term “cell death” is generally a positive in life sciences, but if you were to just pick up the word “death” with an ordinary monitoring platform it would appear as a negative sentiment.
How can companies use your technology to enhance their capabilities?
Opyl is all about digital transformation – using technologies to improve operational efficiencies, mainly through matching, capturing, analysing, using predictive analytics and modelling that can support our clients to make good, evidence-based business decisions and improve clinical trial efficiencies.
Looking ahead, what impact do you think AI-assisted technology will have on the industry?
AI and machine learning technologies are only escalating in scope and impact, so it’s really going to be about all of us becoming more comfortable working with data capture mechanisms and understanding how to effectively apply AI to deliver value.
There’s always conversation about whether this technology will replace jobs, but the reality is that AI technology is an augmenter that relies on human input. Humans to ensure the right data is captured, humans to train the model, humans to interpret the outcomes and how it’s applied.
AI can learn the ‘how’ to do something, but it will never learn the ‘why.’
For more information or to contact Michelle please go to opyl.ai