Sindh, LUMS and AKU Sign Agreement to Integrate AI into Maternal and Child Healthcare
KARACHI, September 25, 2026: The Sindh Health Department, Lahore University of Management Sciences (LUMS), and Aga Khan University (AKU) have signed a three-year Letter of Collaboration to integrate a National AI Hub for Maternal, Newborn and Child Health into Sindh’s public healthcare system.
Supported through a multi-year grant from the Gates Foundation, the initiative aims to bring artificial intelligence-powered tools to frontline healthcare facilities and improve care for women, newborns and children, particularly in underserved communities.
The agreement was signed at the office of Sindh Health and Population Welfare Minister Dr Azra Fazal Pechuho by Health Secretary Tahir Hussain, LUMS Associate Professor Dr Maryam Mustafa, who serves as Hub Director and Principal Investigator, and AKU Medical College Dean Dr Karim Damji.
Dr Anita Zaidi, President of Gender Equality at the Gates Foundation, attended the signing ceremony, along with AKU Associate Professor Dr Zahra Hoodbhoy, whose work includes the development of AI models for point-of-care ultrasound.
Under the partnership, the three institutions will work on risk-stratification models, clinical decision-support systems and voice-enabled AI tools designed to support healthcare workers providing maternal and child health services.
Dr Pechuho said the initiative would focus on primary healthcare facilities, with the aim of improving outcomes for mothers and children.
“I would like to see healthier babies, and prematurity rates go down,” she said, adding that the technology could also help identify congenital conditions and strengthen paramedical services.
The AI Hub builds on several years of collaboration between computer scientists, clinical researchers, epidemiologists and human-centered design specialists. Its clinical research foundation is being led by AKU’s Dr Fyezah Jehan, Chair of the Department of Paediatrics and Child Health.
Her clinical trial networks, maternal and newborn cohort datasets, and field-based epidemiological research will provide real-world evidence for developing and validating predictive AI models. The approach is intended to ensure that the systems are trained using high-quality clinical data and remain relevant to healthcare conditions in resource-constrained settings.
AKU Dean Dr Karim Damji said the partnership would explore how AI could contribute to safer deliveries and better outcomes for mothers and children while keeping solutions cost-effective and efficient.
The technology component of the Hub draws on LUMS’s Awaaz-e-Sehat platform, a voice-enabled electronic record management system initially supported through a Grand Challenges grant. The platform uses localized speech recognition and natural-language technologies to enable health workers, including those operating in low-literacy environments, to interact with digital healthcare systems in local languages.
Dr Maryam Mustafa highlighted the challenge of scaling AI within Pakistan’s healthcare infrastructure, noting that developing technology is only one part of the process. Building the data infrastructure and integrating AI into existing government systems, she said, are essential for large-scale adoption.
The partnership assigns distinct responsibilities to each institution. The Sindh Health and Population Welfare Department will provide strategic oversight, facilitate integration into provincial health facilities and support public-sector deployment. LUMS will lead technical development, algorithm validation, speech technologies and technical safeguards, while AKU will oversee clinical research, safety, field evaluation and implementation.
The collaboration will operate under national regulations, data-privacy requirements and ethical safeguards. The partners have also emphasized that AI tools will be designed to support healthcare professionals rather than replace clinical judgment.
The initiative represents an effort to move AI-powered healthcare beyond research settings and into frontline public health services, with a particular focus on maternal, newborn and child health.