In an era where data drives innovation across industries, Africa’s healthcare sector remains notably underrepresented in the global digital landscape. A Nigerian startup, PBR Life Sciences, is seeking to shift this paradigm by developing and deploying artificial intelligence (AI) models tailored specifically for healthcare data standardisation in low- and middle-income countries. Founded in 2016 by pharmacist and healthcare executive Ayodeji Alaran, PBR Life Sciences is tackling systemic data gaps that have long hindered efficient pharmaceutical logistics, research inclusion, and equitable healthcare delivery in emerging markets.
Ayodeji Alaran, whose professional background includes tenure at global pharmaceutical giants such as GlaxoSmithKline and Pfizer, witnessed first-hand the consequences of data deficiencies. Recurrent challenges included excessive inventory waste due to poor forecasting and inadequate understanding of local disease burdens. This inefficiency, prevalent across many African and Asian markets, highlighted a glaring need for actionable and standardised data to inform drug production and distribution.
Recognising that publicly available healthcare data was both fragmented and inconsistent with international standards, Alaran and his team embarked on building AI models from the ground up. These models were engineered specifically to process and standardise real-world data—spanning patient outcomes, drug efficacy, and regional disease profiles—into formats that align with the World Health Organization’s (WHO) reporting requirements.
Initially, the company struggled with the monumental task of cleaning datasets—some requiring up to nine months of manual processing. Today, thanks to its proprietary algorithms, that same process takes just 20 minutes. This efficiency leap has allowed PBR Life Sciences to reposition itself not just as a data company, but as a critical enabler of clinical research and supply chain optimisation in the global south.
The startup has predominantly used its AI in back-end functions, focusing on operational excellence and data infrastructure. However, with its inclusion in the Google for Startups Growth Academy: AI for Health, PBR Life Sciences is now shifting its focus to the frontlines of healthcare delivery. The aim is to combine its proprietary data assets with Google’s AI and mapping tools to visualise disease prevalence, identify supply-demand gaps, and support targeted interventions in underserved communities. This approach could potentially transform how pharmaceutical companies and public health bodies allocate resources and price medications in real time.
The company’s expansion strategy reflects its commitment to systemic change. With operations already launched in Ghana and Kenya, PBR Life Sciences aims to establish a presence in 20 African countries within the next decade. This geographical diversification is vital to ensuring that African populations are adequately represented in global drug discovery pipelines—particularly as the pharmaceutical industry transitions from traditional clinical trials to data-driven research methodologies.
An important part of this vision includes the upcoming launch of three AI-powered products, including the Health Data Lab. Scheduled for release in June 2025, this initiative is set to create the largest anonymised dataset of Black patients globally. By enabling robust, population-specific research, this dataset seeks to address one of the most pressing gaps in clinical research: the underrepresentation of people of African descent.
Alaran emphasises that while technology drives their capabilities, domain knowledge remains central to the company’s approach. PBR Life Sciences employs a multidisciplinary team comprising pharmacists, clinicians, and data scientists, ensuring that AI outputs are medically relevant and ethically grounded.
As global attention increasingly turns to health equity and inclusive innovation, PBR Life Sciences exemplifies the potential of African-led solutions to reshape global paradigms. Its work underscores a critical truth: that technological advancements in healthcare must be inclusive by design, accounting for all populations, especially those historically left out of the data economy.
