Loubna Bouarfa founded OKRA with the goal of impacting patient lives on a wide scale and supporting the ongoing shift to precision medicine in healthcare - giving the right treatment to the right patient at the right time. Here, she discusses the uptake and importance of AI in healthcare and the impact on healthcare providers, patients and insurers
Today, AI is mainly applied to group patients to different categories, such as subtypes or risk profiles, which are used to find the best treatment for that patient group. This is what we call stratification medicine. When we group patients like this, we mainly focus on urgent cases where patients are already ill, based on direct observation of their symptoms. AI is also currently applied to imaging technology, where it is used to support diagnosis; for example, by detecting signs of skin and breast cancer.
AI can predict whether you will get ill in the first place, and what treatment would be best suited to you
However, this doesn’t use the full power of AI technology. AI can learn from vast quantities of data, detecting hidden patterns and predicting future occurrences based on that data. Essentially, AI can predict whether you will get ill in the first place, and what treatment would be best suited to you. This is precision medicine. OKRA’s AI is designed to support this shift to precision medicine in healthcare, by enabling healthcare professionals to integrate all their data in one place, generate predictions based on patterns in the data, and make evidence-based decisions, all in real time.
All for AI and AI for all
AI is a win-win situation for all healthcare stakeholders: patient, healthcare provider, health authorities, drug provider and insurer. At the moment, we are working with the life sciences industry to maximise precision and speed in decision making, which improves outcomes for patients and reduces costs for the industry. For example, we have predicted how patients will feel about a drug (sentiment reanalysis) in a clinical trial, how drug prescription will shift over time, and what messaging would be most effective for successfully bringing a drug to market. Many pharmaceutical companies are moving from a volume-based to an outcome-based business model, where you don’t pay for the pill but for the outcome.
AI is a win-win situation for all healthcare stakeholders: the patient, healthcare provider, health authorities, drug provider and the insurer
In the longer term, our technology can support clinicians’ decision-making at the point of care, supporting treatment decisions and diagnoses made by hospital staff and general practitioners, and enabling patients to make better informed decisions about their health.
Turning challenges into opportunities
The healthcare industry is changing, which means we face many challenges, but also opportunities. Traditionally, the life sciences industry relies on one-off clinical studies, which are validated with traditional statistics, based on averages in selected patient groups. These studies are not representative of the population at large; for example, only two to four per cent of adult cancer patients participate in clinical trials, and they do not represent the complexities of the real-world environment. With AI, we can move away from the average to the individual, and include all cases instead of just the few that fit the model. This will ensure that every patient receives the best possible treatment. OKRA started on the commercial side, where this change in mindset is easier to achieve, because the business case and benefits are so clear. We are now also working with R&D departments, and are moving to collaborate at the point of care.
Beyond this mindset change, we also face some technical challenges, notably a lack of data integration and the possibulity that there may not be enough data. OKRA can integrate data that ranges from genomic to clinical data, both structured and unstructured, and this requires great technological sophistication. As part of the High-Level Expert Group on AI, we are part of developing recommendations and frameworks that would support a more effective use of health data. Stakeholders must collaborate across the industry, which is challenging, but we are contributing to make this a reality.
Europe’s healthcare system is facing unprecedented pressures … It is clear that more efficiency is needed
Healthcare providers may also feel that AI systems do not give enough explanation behind their output, and worry that their jobs will be replaced by new technology. However, AI is meant to support healthcare professionals in their work, and eliminate routine tasks to free up time. Today, Europe’s healthcare system is facing unprecedented pressures; populations are ageing, chronic diseases are growing, and according to recent estimates, Europe’s healthcare staff will not grow enough by 2020. It is clear that more efficiency is needed.
The OKRA team, our ‘OKRANS’, are working tirelessly to make AI a reality in healthcare and move closer and closer to precision medicine in Europe. We have achieved great things as a team, including recent deliveries for major clients, and winning two awards in less than 24 hours (Best AI Innovation in the Business Weekly Awards, and Best Female-Led Startup in the StartupEurope Awards). At the end of the day, our first priority is to grow – to scale our technology across the life sciences industry, working with technology champions within those companies, and finding the right OKRA employees who want to make a difference for patients.
We are proud to be working with life science technology champions across the globe, who understand that the current gold standard is changing. We collaborate on bringing trustworthy AI to the healthcare industry, to get the right drug to the right patient at the right time. These individuals have a strong track record of taking calculated risks and will be rewarded for it. It is exciting to be partnering with them.
We collaborate on bringing trustworthy AI to the healthcare industry, to get the right drug to the right patient, at the right time
At the same time, many life science companies are attempting to build their AI capacities in-house, rather than taking help from vendors and experts. There is a degree of scepticism, where executives feel more in control by keeping their technology under one roof. However, this creates several problems: the data scientist's job is often limited to creating those one-off studies, which prevents AI from achieving its full potential, and in-house staff may lack expertise in deployment of AI given all the ethical requirements such as continuous bias prevention and interpretability of AI systems output. On a European level, I would like to see more initiatives that educate business leaders on the complexity of AI systems, and facilitate dialogue between leaders and AI experts, so we can form even better collaborations. Startups such as OKRA are flexible and can develop their technology much faster and we should make full use of this.
I am also honoured to be part of the European Union High-Level Expert Group on AI. Europe is taking the lead on an ethical discussion around the regulation of AI, which will be crucial for inspiring trust within the healthcare industry.
The future is AI
Over the long term, AI will move healthcare from passive to proactive; instead of waiting to get ill before we get treated, we will predict and prevent our health issues. The healthcare system will flag us for tests and check-ups, identify the best treatments and physicians, and empower patients to manage their health. I already see real results, and am optimistic that more stakeholders will catch up with the frontrunners of today. ■