Collaboration aims to modernize diagnostic workflows, strengthen pathology capabilities and lay the foundation for broader access to timely, reliable and equitable services
VIA GRAPHIC PLUS | TAGUIG CITY, Philippines — AstraZeneca Philippines and Hi-Precision Diagnostics Center, Inc. have signed a memorandum of understanding to advance digital and computational pathology in the Philippines, beginning with implementation at Hi-Precision Diagnostics and with the potential to inform adoption across relevant care settings.
Digital pathology converts glass slides from a patient’s tissue sample into high-resolution images that pathologists can securely review and share with specialists [1,2]. Computational pathology uses validated software, including artificial intelligence, to highlight patterns that support, but do not replace, the pathologist’s diagnosis. For every Filipino cancer patient, reaching the right diagnosis at the right time is critical because it helps care teams identify appropriate treatment options without unnecessary delay [3,4].
For Filipino patients, particularly those with cancer who live far from specialist centers, responsible use of these technologies could make expert case review and second opinions easier to access, improve laboratory workflow, and provide care teams with timely diagnostic information that supports precision medicine by helping match each patient to the most appropriate available treatment based on the characteristics of their disease [2–4].
“Every patient deserves timely, accurate diagnostics that can help guide the right care. Through our collaboration with Hi-Precision Diagnostics, we aim to combine science, technology and local expertise to strengthen pathology services and help build a more connected, equitable and future-ready diagnostic ecosystem for the Philippines,” said Lotis Ramin, Country President, AstraZeneca Philippines.
Under the MOU, the parties intend to modernize digital pathology infrastructure and workflows through deployment, optimization and systems interoperability; strengthen clinical quality and workforce capability through validation, quality assurance, governance, training and knowledge-sharing; and support responsible, equitable and sustainable delivery through robust data governance, appropriate collaborative review and remote consultation, and ongoing performance monitoring and continuous improvement.
“Hi-Precision has always believed that quality diagnostics should be accurate, accessible and responsive to patients’ needs. This collaboration with AstraZeneca will help us strengthen the capabilities, standards and systems required for digital pathology, while equipping our teams to deliver dependable diagnostic services in an increasingly connected healthcare environment,” said Vannessa Ongsue, Vice President for Medical Services, Hi-Precision Diagnostics.
By building the infrastructure, skills and governance needed for digital pathology, the partners aim to create a strong foundation for responsible innovation and broader access to high-quality pathology services.
Together, AstraZeneca and Hi-Precision are helping future-proof oncology diagnostics and unlock a new era of more connected, precise and patient-centered cancer care for Filipinos.
References
- Kumar, N., Gupta, R., & Gupta, S. (2020). Whole slide imaging (WSI) in pathology: Current perspectives and future directions. Journal of Digital Imaging, 33(4), 1034–1040. https://doi.org/10.1007/s10278-020-00351-z
- Hanna, M. G., Reuter, V. E., Ardon, O., Tan, K. S., Pham, T., Sirintrapun, S. J., Schüffler, P. J., Corsale, L., Brogi, E., Busam, K. J., Klimstra, D. S., & Evans, A. G. (2020). Validation of a digital pathology system including remote review during the COVID-19 pandemic. Modern Pathology, 33(11), 2115–2127. https://doi.org/10.1038/s41379-020-0601-5
- Cui, M., & Zhang, D. Y. (2021). Artificial intelligence and computational pathology. Laboratory Investigation, 101(4), 412–422. https://doi.org/10.1038/s41374-020-00514-0
- van der Laak, J., Litjens, G., & Ciompi, F. (2021). Deep learning in histopathology: The path to the clinic. Nature Medicine, 27(5), 775–784. https://doi.org/10.1038/s41591-021-01343-4
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