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Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors

Award Number: R01AI146028
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Project Summary Scientific understanding of adaptive immune receptors (i.e. antibodies and T cell receptors) has the potential to revolutionize prophylaxis, diagnosis, and treatment of disease. High‐throughput DNA sequencing and functional experiments have now brought the study of adaptive immune receptors into the big‐data era. To realize this potential of these data they must be matched with appropriately powerful analytical techniques. Existing probabilistic and mechanistic models are insufficient to capture the complexities of these data, while a naïve application of machine learning cannot leverage our profound existing knowledge of the immune system. The goal of this project is to blend deep learning with mechanistic modeling in order to predict and understand the evolution and function of adaptive immune receptors. Aim 1: Develop generative models of immune receptor sequences that capture the complexity of real adaptive immune receptor repertoires. These will combine deep learning along with our knowledge of VDJ recombination, and provide a rigorous platform for detailed repertoire comparison. Aim 2: Develop quantitative mechanistic models of antibody somatic hypermutation that incorporate the underlying biochemical processes. Estimate intractable likelihoods using deep learning to infer important latent variables, and validate models using knock‐out experiments in cell lines. Aim 3: Develop hybrid deep learning models to predict binding properties from sequence data, combining large experimentally‐derived binding data with even larger sets of immune sequences from human immune memory samples. Incorporate structural information via 3D convolution or distance‐based penalties. These tools will reveal the full power of immune repertoire data for medical applications. We will obtain more rigorous comparisons of repertoires via their distribution in a relevant space. These will reveal the effects of immune perturbations such as vaccination and disease, allowing us to pick out sequences that are impacted by these perturbations. We will have a greater quantitative understanding of somatic hypermutation in vivo, and statistical models that appropriately capture long‐range effects of collections of mutations. We will also have algorithms that will be able to combine repertoire data and sparse binding data to predict binding properties. Put together, these advances will enable rational vaccine design, treatment for autoimmune disease, and identification of T cells that are promising candidates for cancer immunotherapy.


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: 2024 ( Subtotal = $689,648 )
2024	2024	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	6	5/31/2024	NON-COMPETING CONTINUATION	$689,648
														Subtotal = $689,648

Issue Date FY: 2023 ( Subtotal = $0 )
2023	2022	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	5	6/2/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2022 ( Subtotal = $689,648 )
2022	2022	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	002	5	7/14/2022	NON-COMPETING CONTINUATION	$666,480
2022	2022	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	006	5	9/27/2022	NON-COMPETING CONTINUATION	$85,050
2022	2022	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	003	5	8/17/2022	NON-COMPETING CONTINUATION	$23,168
2022	2021	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	001	4	5/27/2022	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$689,647
2022	2021	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	005	3	9/27/2022	NON-COMPETING CONTINUATION	-$1
2022	2021	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	3	5/27/2022	NON-COMPETING CONTINUATION	-$689,647
2022	2020	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	004	2	9/27/2022	NON-COMPETING CONTINUATION	-$85,049
														Subtotal = $689,648

Issue Date FY: 2021 ( Subtotal = $689,648 )
2021	2021	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	001	3	6/16/2021	NON-COMPETING CONTINUATION	$0
2021	2021	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	3	6/1/2021	NON-COMPETING CONTINUATION	$689,648
														Subtotal = $689,648

Issue Date FY: 2020 ( Subtotal = $710,049 )
2020	2020	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	2	5/5/2020	NON-COMPETING CONTINUATION	$710,049
														Subtotal = $710,049

Issue Date FY: 2019 ( Subtotal = $632,498 )
2019	2019	FRED HUTCHINSON CANCER RESEARCH CENTER	1100 FAIRVIEW AVE N J6-300	SEATTLE	WA	98109	KING	USA	Allergy and Infectious Diseases Research	000	1	5/30/2019	NEW	$632,498
														Subtotal = $632,498

Grand Total All Awards = $3,411,491

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Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptors

Award Number: R01AI146028

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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