# SCH: INT: Collaborative Research: Development and analysis of new mathematical and statistical models for chronic pain

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2020 · $368,508

## Abstract

Program Director/Principal Investigator (Last, First, Middle): Abrams, Daniel, M
Project Description
 1. Intellectual merit
(see Sec. 2, pages 13-14, for "Broader impacts")
1.1 Introduction and background
1.1.1 General introduction
During recent decades there has been an extraordinary growth in the availability of data relating
to a wide range of microbiological systems. That data has enabled new quantitative approaches
to biology, including the development of new mathematical and statistical models that given fun-
damental insight into the workings of biological systems.
 Another source is now growing explosively: biomedical data. This data has significant potential
for use in treatment of human disease, but thus far comparatively fewer mathematical models for
medical phenomena have been developed. The hope is that quantitative models will allow for
"personalized" or "precision" medicine, where treatment protocols are customized based on an
understanding of how individual patient characteristics impact the effectiveness of the treatment.
Deep mathematical understanding of biomedical systems also promises to allow for optimization
of medical interventions: the physical and/or financial costs of intervention could be minimized for
a given desired level of benefit.
 The broad goal of the proposed research is to develop new integrative mathematical models for
the dynamics of subjective pain in patients suffering from chronic pain. These models will combine
existing qualitative knowledge with insight gained from newly available patient data, with the goal
of incorporating data streams corning on line in the near future. We plan to develop multiple models
in parallel using a variety of approaches and then to select the best rnodel(s) based on agreement
with objective data.
1.1.2 Background on biological application: Sickle cell disease
Sickle cell disease (SCD) is a chronic illness associated with frequent medical complications and
hospitalizations. Approximately 90% of acute care visits are for pain events, and 30-day reuti-
lization rates are alarmingly high [27]. While factors influenci.ng these high re-utilization rates are
poorly understood, close follow-up and continued use of pain medication has been shown to de-
crease re-hospitalization rates. Mobile technology has become an integral part of health care
management and Pl Shah's recently developed mobile application (SMART app - see Figure 1)
for SCD assists with documentation of pain and interventions.
1.1.3 Background on hybrid approach
Perhaps because of the often distinct educational backgrounds of practitioners or distinct typical
applications, statistical and mechanistic approaches are not frequently combined in addressing a
single problem. The majority of attempts in the scientific literature have appeared in the context
of neural networks [37, 38, 29] and chemical engineering [38, 33, 11], where they largely play
a computational rather than analytical role. Some attempts have also been...

## Key facts

- **NIH application ID:** 10180356
- **Project number:** 3R01AT010413-03S1
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Daniel M Abrams
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $368,508
- **Award type:** 3
- **Project period:** 2018-09-13 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10180356

## Citation

> US National Institutes of Health, RePORTER application 10180356, SCH: INT: Collaborative Research: Development and analysis of new mathematical and statistical models for chronic pain (3R01AT010413-03S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10180356. Licensed CC0.

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