Africa-Press – Eswatini. Ayodeji Alaran, founder and CEO of PBR Life Sciences, started his career as a trained pharmacist. He gained experience working with global pharmaceutical companies such as GlaxoSmithKline and Pfizer across Africa and Asia. During his tenure, he witnessed the significant losses caused by a lack of reliable data.
A recurring issue was that pharmaceutical companies were left with large volumes of expired inventory, primarily due to the absence of accurate data to forecast disease trends and determine the necessary quantity of medicines to manufacture or import into various countries.
This insight led to the founding of PBR Life Sciences in 2016.
Although healthcare data was available, cleaning and analyzing it to meet global standards proved challenging. As a result, he started developing AI models from the ground up, focusing on data standardization.
As Ayodeji joins the third cohort of the Google for Startups’ Growth Academy: AI for Health program , he reflects on the pivotal moments, lessons, and breakthroughs that have shaped his journey, along with what’s yet to come.
Training and building AI models transformed everything for us
At first, we searched for AI algorithms trained on African healthcare data but couldn’t find any, so we had to create our own. Initially, cleaning a dataset would take us eight to nine months, but with our proprietary AI models, it now takes just 20 minutes
We now use AI for data standardization to meet WHO requirements, as most of our data is real-world data. However, even with advanced technology and AI models, domain knowledge remains crucial. Our backend team includes doctors, pharmacists, and experienced scientists who possess practical knowledge of diseases and drugs, ensuring the accuracy and relevance of our work.
AI powered our backend, and now we are shifting it to the frontline
Until now, most of our AI deployment has been in the back office, focusing on operational excellence. However, with our inclusion in the Google for Startups program, we are now shifting our focus to unlocking greater value for our customers and patients.
For example, we are exploring the possibility of combining our proprietary data with Google’s AI to visualize disease prevalence, pinpoint areas with supply gaps, or intervene in regions where pricing is poorly managed.
Integrating solutions like Google Maps could enable healthcare workers and pharmaceutical companies to effectively map opportunities in a practical manner.AI is driving our growth as we scale in emerging markets
The challenges we are addressing extend beyond individual countries, affecting emerging markets as a whole. Additionally, as global pharmaceutical companies move from traditional clinical trials to utilizing big data and AI for drug discovery, we’ve recognized that patients in emerging markets are often excluded from this data, potentially leading to medications developed without considering these populations.
To address this, we’re scaling up to build more comprehensive data sets. For example, we’ve recently expanded into Ghana and Kenya. Our aim is to be present in 20 countries over the next 10 years, ensuring that these markets are represented in drug discovery, pricing, and the introduction of new technologies.
This June, we’re launching three new AI-powered products, including the Health Data Lab, which will feature the largest anonymized dataset of Black patients globally, aimed at enhancing clinical research.
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