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Multimodal machine learning for diagnosis and mechanistic phenotyping of inherited diseases

Award Number: OT2OD037960
ORGANIZATION: OFFICE OF THE DIRECTOR, NIH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: OTHER
PERIOD OF PERFORMANCE START DATE: 06/06/2025
PERIOD OF PERFORMANCE END DATE: 06/05/2027

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Multimodal machine learning for diagnosis and mechanistic phenotyping of inherited diseases - ABSTRACT Inherited diseases frequently manifest with distinctive facial features, collectively referred to as the “facial gestalt.” However, the effectiveness of using facial information relies heavily upon the clinician's breadth of experience, and such reliance often leads to delays in diagnosing patients. Furthermore, 1 in 600 newborns have craniofacial anomalies, impacting the skull, jaws, ears and/or teeth. Improved therapeutic approaches require a deep understanding of the molecular and biological systems underlying these craniofacial conditions. Through an interdisciplinary and agile team, our study has two objectives: (1) We will develop an ethically focused and data-driven multimodal machine learning algorithm that integrates frontal facial photos, clinical notes, patient demographics, and structured phenotypes to improve diagnosis of genetic syndromes. (2) We will develop a multimodal algorithm that takes 4D videos (non-invasive laser scanning to map craniofacial surface morphology), facial photos, electronic health records, and omics information (genome, transcriptome and epigenome), to prioritize genes in key pathways that are relevant to phenotypic features of craniofacial abnormalities. We will adapt a patient/clinician engaged design, ensuring that the training data and outcome evaluation metrics align closely with real-world applications. We will develop a modularized open-source software to decouple the multimodal approach from the underlying pretrained models, ensuring that the final product is adaptable to rapid changes in AI technologies to be easily integrated into evolving healthcare landscapes. Our project addresses the social-technological challenges in clinical diagnosis of rare diseases, to advance understanding, interpretation and prediction of complex biological, behavioral, and health manifestations through the implementation of multimodal approaches.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $1,217,898 )
2026	2026	THE CHILDREN'S HOSPITAL OF PHILADELPHIA	3401 CIVIC CENTER BLVD	PHILADELPHIA	PA	19104	PHILADELPHIA	USA	Trans-NIH Research Support	002	1	6/3/2026	SUPPLEMENT FOR EXPANSION	$1,217,898
2026	2025	THE CHILDREN'S HOSPITAL OF PHILADELPHIA	3401 CIVIC CENTER BLVD	PHILADELPHIA	PA	19104	PHILADELPHIA	USA	Trans-NIH Research Support	000	1	2/24/2026	NEW	$0
2026	2025	THE CHILDREN'S HOSPITAL OF PHILADELPHIA	3401 CIVIC CENTER BLVD	PHILADELPHIA	PA	19104	PHILADELPHIA	USA	Trans-NIH Research Support	001	1	6/3/2026	NEW	$0
														Subtotal = $1,217,898

Issue Date FY: 2025 ( Subtotal = $1,156,956 )
2025	2025	THE CHILDREN'S HOSPITAL OF PHILADELPHIA	3401 CIVIC CENTER BLVD	PHILADELPHIA	PA	19104	PHILADELPHIA	USA	Trans-NIH Research Support	000	1	6/6/2025	NEW	$1,156,956
														Subtotal = $1,156,956

Grand Total All Awards = $2,374,854

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Multimodal machine learning for diagnosis and mechanistic phenotyping of inherited diseases

Award Number: OT2OD037960

ORGANIZATION: OFFICE OF THE DIRECTOR, NIH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: OTHER

PERIOD OF PERFORMANCE START DATE: 06/06/2025

PERIOD OF PERFORMANCE END DATE: 06/05/2027

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