GenAI in healthcare: Helping the people who deliver care, therapies and research

Healthcare is rapidly evolving and AI is at the forefront of this movement. There are three key opportunities for AI in healthcare. We can harness it to:

• Enhance healthcare productivity and efficiency
• Transform health with personalised and predictive care
• Empower patients and improve health outcomes

At Huma, we have always believed in the potential AI has to offer. This is why we have made strategic acquisitions of AI health companies and their AI model patents, which has given us a wealth of knowledge and expertise in this area.

We have also been building proof-of-concept AI models, for a number of years, and publishing them in peer-reviewed journals. This has allowed us to demonstrate the potential AI has in advancing healthcare to the next level.

AI in healthcare

1 million nurses in the US are predicted to leave the workforce by 2027. Nurses are feeling burned out, fatigued and drained. They’re spending 25% of their time on admin tasks like documentation and paper charting, leaving less time for doing what they most likely joined medicine for: caring for patients.?

AI-powered tools can alleviate administrative burden and enhance efficiency for healthcare professionals. In certain deployments in the US, Huma's platform uses GenAI models to generate concise patient notes summaries from patients’ own data points. These notes can be quickly reviewed and edited, saving healthcare professionals valuable time.

We are also developing integration of GenAI to personalise clinician to patient messaging. Healthcare providers can create personalised, relevant messages for their patients in seconds. This can help increase patient engagement and improve self care management.?

AI has the potential to promote proactive patient engagement and accessibility, to relieve? overburdened healthcare systems. In the UK, more than 18 million GP appointments and 2.1 million visits to A&E are for self-treatable conditions, costing the NHS more than ￡850 million a year. myGP's skin scanner, powered by AUTODERM’s AI technology, is a great example of how iPLATO, a Huma company, harnesses emerging technology to provide innovative solutions.

AI in pharma

AI has far reaching potential to transform health in the pharmaceutical sector.

Take preventative health for example. Huma has partnered with Bayer, helping to develop the Bayer Aspirin Heart Risk Assessment. Huma developed an algorithm using data from the UK's Biobank which predicts long-term risk of cardiovascular disease. Through a user-friendly questionnaire, individuals can determine whether they fall into higher, average, or lower risk categories for developing CVD.?

Combining the capabilities of Huma's FDA Class II platform (which allows clinicians to set specific thresholds and develop personalised treatment plans) with AI will lead to further initiatives in predictive health.

AI in clinical research

Deeply rooted in clinical research, Alcedis Labs forms an integral component of the Alcedis IT department. Its primary mission involves tackling real-world challenges and designing AI software products that are instrumental in day-to-day clinical research activities. Through our extensive collaboration with various departments, we consistently bring tangible value to our customers, prioritising their needs above all else.?

Alcedis Labs' AI software solutions work alongside researchers to improve clinical data input and processing accuracy. This helps streamline study processes, mitigate risks, and enhance operational efficiency. Clinicians can then focus their resources on more meaningful tasks to accelerate treatment delivery to patients.

Building safe and effective AI models for preventive, predictive and proactive care

Huma has been developing proof of concept AI models and submitting for publication for a number of years for both care and research. This includes:?

Development of Digitally Obtainable 10-Year Risk Scores for Depression and Anxiety in the General Population: The aim of the study was to “build prediction models for depression and anxiety, with a specific focus on factors linked to digitally-obtainable data. Using a data-driven approach to feature selection and model optimisation, we trained models for prediction of depression and anxiety using both traditional statistical and machine learning methods.”

A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set: The study “aimed to conduct an external validation of the C-Score in the US population and expand the original score to improve its predictive capabilities in the US population. The C-Score is intended for mobile health apps on wearable devices.”

We are committed to building AI models in a safe and effective way across preventive, predictive and proactive care.? We have a proven track record of building peer-reviewed proof of concepts for AI, and we will continue to do so as we move into evaluating the potential benefits of AI in healthcare, now and in the future.

Huma and Google Cloud

This week we announced a collaboration with Google Cloud to use GenAI to enhance our regulated disease management platform. We are exploring the use of Google’s GenAI tools, including Med-PaLM 2, a large language model developed and trained on a variety of dense medical texts, to improve patient engagement and boost the clinical capacity of healthcare professionals, providing them with better insights to optimise care delivery.

We are well positioned to evaluate the value GenAI applications can bring to healthcare in a safe manner with a ‘human in the loop’, in this case a qualified nurse or a clinician who can assess, validate and adjust any AI outputs with appropriate guardrails in place. Our platform currently uses AI models to analyse patient data and provide insights that can help clinicians make better decisions.?

Now, with Huma’s access to Google Cloud’s Vertex AI platform and other GenAI tools such as PaLM 2 and Med-Palm 2, Huma will develop a pipeline of use cases to make the platform even more impactful for providers and patients to drive better care delivery and outcomes.?

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