The pivotal role of AI in transforming drug repurposing for neglected diseases in Southeast Asia

Since the onset of the pandemic, the healthtech industry in Southeast Asia has been rapidly accelerating as people increasingly recognise the importance of preventative and restorative healthcare. However, developing a novel drug remains complex and time-consuming, typically requiring at least ten years and USD 2.6 billion from initial discovery to market.

Pharmaceutical companies rely on patents to be the sole supplier of a new drug in a country, justifying these significant investments of time and resources. In this context, cutting-edge technologies like artificial intelligence (AI) offer the potential to significantly reduce the cost of medicine and improve the industry’s efficiency.

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The use of AI in drug repurposing efforts, particularly for neglected diseases that often lack sufficient research funding, is proving to be a beacon of hope, offering new possibilities and solutions.

Rapid identification of new drug uses

As the use of artificial intelligence rises, identifying drugs will take a shorter time to analyse, which will be effective and efficient in combating diseases like dengue or tuberculosis. In drug discovery, it facilitates virtual screening by efficiently analysing vast chemical libraries to identify candidates likely to bind to specific targets.

Then, it establishes links between compounds’ chemical structures and biological activity, enabling researchers to design molecules with high potency, selectivity, and favourable pharmacokinetic profiles.

Finally, it employs reinforcement learning and generative models to propose novel drug-like chemical structures, expanding the chemical space and driving the development of innovative drug candidates.

Reducing costs and time in drug development

Traditional drug discovery is a costly and lengthy process, often requiring years of research and billions of dollars before a drug is suitable for launching on the market. This challenge becomes even more pressing during critical times, such as those experienced during the COVID-19 pandemic, when there is an urgent need for effective medications.

AI-driven drug repurposing addresses this issue using machine learning techniques and advanced algorithms to identify new therapeutic uses for existing compounds rapidly. This usage reassures us that AI is not just a buzzword. It offers a practical solution that can swiftly screen existing drugs against new disease targets, accelerating the identification of potential therapies.

Predicting treatment outcomes with greater accuracy

Sophisticated AI-powered predictive models can simulate how a repurposed drug will interact with the body, allowing researchers to predict both efficacy and potential side effects. With their high accuracy, these predictive models also help researchers prioritise the most promising drug candidates for clinical trials, especially for diseases with limited research funding. 

This confidence in the accuracy of AI models is a game-changer and brings hope for significant advancement in medical research in many different sectors.

Enhancing access to treatments for underserved populations

Underserved populations, particularly those in rural and remote areas, something all too familiar to many of ASEAN’s countries, often struggle with limited access to affordable and effective medications. Logistical challenges, economic constraints, and a lack of tailored healthcare solutions exacerbate this disparity.

AI technology presents a transformative opportunity to address these challenges by offering more personalised and region-specific drug development and distribution approaches. Data models can be trained on information specific to underserved regions, taking into consideration factors such as local disease burdens, genetic variations, and socioeconomic conditions.

Pinpointing an area’s particular requirements allows the creation of more relevant and impactful treatments for these populations, ensuring that the medications developed are better suited to their unique needs.

Additionally, AI-powered telemedicine platforms can extend the reach of healthcare services to remote areas, allowing patients to consult with doctors for medical advice and have remote follow-up care without the need to travel long distances.

Improving personalised medicine for diverse populations

In Southeast Asia, where populations are highly diverse, personalised medicine offers the potential for more effective and individualised medical treatments. Unlike standard medical approaches that target the average patient, precision medicine tailors treatments and vaccines to specific genetic profiles, environmental factors, and lifestyles.

Using AI is a considerable advancement in this process, as it customises drugs and repurposes efforts to address the unique genetic and ecological aspects of Southeast Asian populations. For example, one company is working to analyse a patient’s medical history and genetic data to find the most suitable antidepressant and dosage. This process involves exposing the patient’s brain cells to various antidepressants to identify biomarkers, ensuring effective treatment.

The recent integration of AI technology in the healthcare sector is revolutionising how treatments are developed and delivered, particularly in Southeast Asia. By harnessing machine learning for drug repurposing, researchers can quickly identify new therapeutic uses for existing medications, offering faster and more cost-effective solutions, especially for neglected diseases overlooked for too long.

Using this approach enhances drug development efficiency. It also moves governments closer to ensuring that vital treatments reach underserved populations, addressing both current healthcare needs and future challenges.