The Health Department of the Government of Sindh, the Lahore University of Management Sciences (LUMS) and the 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 the public health system. This will bring artificial intelligence to frontline care to improve health indicators for the most vulnerable women and children.
The agreement was signed at the office of Sindh Minister for Health and Population Welfare Dr Azra Fazal Pechuho on Wednesday, September 2, 2026, by Health Secretary Tahir Hussain, Associate Professor Dr Maryam Mustafa, Hub Director and Principal Investigator at LUMS, and Dr Karim Damji, the Dean of the Medical College at AKU.
Dr Anita Zaidi, President of Gender Equality at the Gates Foundation, was present at the signing. The Gates Foundation is supporting the Hub through a multi-year grant. Also, present was AKU Paediatrics & Child Health Associate Professor Dr Zahra Hoodbhoy who has been working on point-of-care ultrasound AI models.
The three institutions will jointly roll out risk-stratification models, clinical decision-support systems, and voice-assisted tools for frontline care frontline care providers delivering maternal and child health services
Dr Azra Pechuho said she was targeting primary health facilities in this initiative. “I would like to see healthier babies, and prematurity rates go down,” she said, adding that she hoped it would help identify congenital problems and improve paramedical services as well.
The Hub is a culmination of a multi-year collaboration between computer scientists, human-centered design experts, and clinical epidemiologists. Its clinical backbone comes from the work of AKU’s Dr Fyezah Jehan, Chair of the Department of Paediatrics and Child Health who is the Lead for the Hub’s Clinical Research. Her clinical trial networks, maternal-newborn cohort datasets, and field-based epidemiological research provide the real-world clinical validation required to train accurate predictive algorithms, ensuring the AI models are built on high-quality clinical data and responsive to the realities of healthcare delivery in low-resource settings.
“We have brilliant faculty and that’s the magic,” said AKU’s Dean Karim Damji after signing. “I think it’s fantastic because we are serving people better, in this case maternal, newborn, child health, and looking at ways to understand what value we can offer for safer deliveries for the mothers, but also for the children. We have to embrace [AI] and try to make it as cost effective and efficient as possible.”
The Hub’s technology builds on Dr Maryam Mustafa’s pioneering Awaaz-e-Sehat, a voice-enabled electronic record management platform first funded under a Grand Challenges grant. Her team’s work in localized speech recognition and natural language architectures–designed for low-literacy environments–lets frontline health workers interact with AI tools seamlessly in their own languages.
“One of the things that worries me the most as a computer scientist working in AI and health is that Pakistan is far, far behind other countries when it comes to adopting AI tools,” said Dr Maryam Mustafa. “And part of the reason is that we don’t have a formalized data infrastructure that can help scale AI tools. The tech part is actually easier to build. It is how do you embed it in existing infrastructures and get governments to adopt and scale.” Even the most remote areas should have access to these tools.
How the partnership works
Health and Population Welfare Department, Government of Sindh: Provides strategic oversight, provincial facility integration, alignment with national health policies, and public sector deployment.
LUMS: Serves as Technical Partner, leading model development, algorithm validation, speech technologies, and technical safeguards.
AKU: Acts as the clinical, research, and implementation partner, guiding clinical safety, real-world trial evaluation, and field translation across primary care facilities.
The cooperation adheres strictly to national regulatory standards, data privacy guidelines, and ethical safeguards, with a core commitment that AI solutions assist, never replace, clinical judgment.
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