Applications of artificial intelligence in the pharmaceutical industry

Founded in 2019, Alto Neuroscience is a clinical-stage biopharmaceutical start-up that uses its AI-enabled platform to measure brain biomarkers, including electroencephalogram (EEG) activity and behavioural patterns, wearable data, genetics, and other factors to drive targeted drug development in mental health.

Alto Neuroscience has several drugs in clinical development, including three in Phase II studies for major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) (ALTO-100, ALTO-202, and ALTO-300) and four in Phase I for unspecified psychiatric disorders.

In October 2021, Alto Neuroscience announced that it had raised $40m in funding to advance its drug development process, including $8m in a seed funding round, and $32m in a Series A round led by Apeiron Investment Group.

In December 2021, Cerebral, a mental health start-up, and Alto Neuroscience announced a partnership to launch a decentralised clinical study in precision psychiatry to boost drug development and treatments for patients with mental disorders. The companies joined forces to conduct a Phase II clinical trial for Alto Neuroscience’s ALTO-300 depression drug candidate, and around 100 participants from Cerebral’s member network were enrolled from January 2022.

Participants undergo in-home evaluations measuring their brain activity, sleep, activity patterns, and genetics, as well as clinical outcomes such as depression and PTSD. Using Alto Neuroscience’s analytical approach to predicting patient outcomes, it will assess whether certain biomarkers are the best way to identify patients most likely to benefit from a given drug candidate. The Phase II study is expected to complete in June 2023.

In January 2023, Alto Neuroscience announced positive results for a Phase IIa trial of ALTO-100, a new drug for MDD. The trial recruited 228 patients with MDD or PTSD, of which 59 had an MDD biomarker profile that Alto identified as predicting drug efficacy. The trial's primary endpoint was a change in depression severity compared to baseline after six weeks. The biomarker-defined patients saw a greater reduction in the clinical assessment used for this compared to those without.

For clinical response, defined as a 50% reduction in symptoms of depression, a higher number of biomarker-defined patients (61%) achieved the desired result compared to patients without (33%). The trial is now in Phase IIb, focused solely on biomarker-defined patients to further demonstrate patient safety and efficacy.

The Phase IIb trial has been supported by a $35m Series B funding led by Lightswitch Capital and partners of Alkeon Capital secured in October 2022, and a further $25m equity investment added to the Series B fund by Alpha Wave Ventures in January 2023. Alto Neuroscience also entered into a $35m credit facility with K2 HealthVentures in 2023. The proceeds will be used to expand and continue the development of other mental-health-related therapeutics.

California-based enterprise analytics start-up Clarify Health Solutions (Clarify Health) has launched a closed beta of its GenAI copilot dubbed Clara. It is based on the startup’s Clarify Atlas platform that maps over 300 million patient journeys to deliver more than 18 billion AI-powered predictions and surface insights with speed and precision. 
  
The copilot leverages Clarify’s healthcare claims dataset and employs advanced ML and NLP to deliver precise, relevant, and actionable data to healthcare professionals. It enables organisations to gain insights into influenceable behaviour changes that are pivotal in lowering healthcare costs and improving the quality of care. Users can access these insights instantly reducing the time for decision making.

Incentivised, higher-value care decisions can lead to better patient care and reduced costs. These strategies include pay-for-performance programs, bundled payments, shared savings models, value-based insurance design, patient education and decision support, and health information technology. Implementing these approaches requires collaboration among healthcare providers, payers, policymakers, and patients to align financial incentives with improved outcomes and cost-effectiveness. 
  
Healthcare providers are always aiming to reduce costs, improve efficiency, and enhance patient outcomes. Clarify Health aims to empower organisations to identify opportunities to encourage and incentivise decisions that lead to higher-quality care and lower costs for patients by utilising Clara.

In April 2022, the start-up raised $150m in Series D funding led by SoftBank Vision Fund 2 along with other existing investors. It intended to utilise these funds to strengthen its clinical informatics capabilities and broaden its value-based payments technology. Clarify Health anticipates that Clara can transform the healthcare delivery landscape by offering organisations the opportunity to shape their development and tailor their capabilities to their unique needs.

Japan’s REPROCELL, in collaboration with IBM and STFC Hartree Centre, has launched Pharmacology-AI, a platform designed to simplify and accelerate the analysis of big data from drug development studies. The platform aims to help researchers identify inter-individual differences that significantly influence drug response or related clinical outcomes. It is designed to make the process of finding actionable insights from data quicker and easier, without the need for bioinformatics expertise. 
  
Pharmacology-AI platform uses AI to analyse large datasets related to precision medicine. It simplifies analysis of large datasets, enabling researchers to quickly and easily reveal the genomic or clinical features driving drug response data, biomarker levels, or other clinical data outcomes.

The platform provides AI analysis outputs in an easily interpretable and interactive format via a secure web portal built in compliance with industry standards. It also allows for the combination of analysis with preclinical human tissue research to enhance translational data sets and increase the chances of clinical success. 
  
Conventional analysis of large datasets in precision medicine can be time-consuming and complex, requiring high-level bioinformatics expertise. Pharmacology-AI addresses this challenge by employing AI. The platform can help improve the design of clinical trials, making them more successful and less costly.

It can also help identify patient populations most likely to benefit from new drugs much earlier in the drug development process. Furthermore, it can reveal why some patients respond to commonly prescribed drugs, while others gain little or no benefit. This could lead to more personalised treatment plans and improved patient outcomes. REPROCELL plans to expand the use of this technology across various organ systems and therapeutic areas.