Toward mechanistic medical digital twins: some use cases in immunology.

A fundamental challenge for personalized medicine is to capture enough of the complexity of an individual patient to determine an optimal way to keep them healthy or restore their health. This will require personalized computational models of sufficient resolution and with enough mechanistic information to provide actionable information to the clinician. Such personalized models are increasingly referred to as medical digital twins. Digital twin technology for health applications is still in its infancy, and extensive research and development is required. This article focuses on several projects in different stages of development that can lead to specific-and practical-medical digital twins or digital twin modeling platforms. It emerged from a two-day forum on problems related to medical digital twins, particularly those involving an immune system component. Open access video recordings of the forum discussions are available.

Forum on immune digital twins: a meeting report.

Medical digital twins are computational models of human biology relevant to a given medical condition, which are tailored to an individual patient, thereby predicting the course of disease and individualized treatments, an important goal of personalized medicine. The immune system, which has a central role in many diseases, is highly heterogeneous between individuals, and thus poses a major challenge for this technology. In February 2023, an international group of experts convened for two days to discuss these challenges related to immune digital twins. The group consisted of clinicians, immunologists, biologists, and mathematical modelers, representative of the interdisciplinary nature of medical digital twin development. A video recording of the entire event is available. This paper presents a synopsis of the discussions, brief descriptions of ongoing digital twin projects at different stages of progress. It also proposes a 5-year action plan for further developing this technology. The main recommendations are to identify and pursue a small number of promising use cases, to develop stimulation-specific assays of immune function in a clinical setting, and to develop a database of existing computational immune models, as well as advanced modeling technology and infrastructure.

A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation.

Adaptive therapy is a dynamic cancer treatment protocol that updates (or 'adapts') treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific dose modulation or dose timing. Adaptive therapy maintains high levels of tumor burden to benefit from the competitive suppression of treatment-sensitive subpopulations on treatment-resistant subpopulations. This evolution-based approach to cancer treatment has been integrated into several ongoing or planned clinical trials, including treatment of metastatic castrate resistant prostate cancer, ovarian cancer, and BRAF-mutant melanoma. In the previous few decades, experimental and clinical investigation of adaptive therapy has progressed synergistically with mathematical and computational modeling. In this work, we discuss 11 open questions in cancer adaptive therapy mathematical modeling. The questions are split into three sections: (1) integrating the appropriate components into mathematical models (2) design and validation of dosing protocols, and (3) challenges and opportunities in clinical translation.

A Mathematical Model of T1D Acceleration and Delay by Viral Infection.

Type 1 diabetes (T1D) is often triggered by a viral infection, but the T1D prevalence is rising among populations that have a lower exposure to viral infection. In an animal model of T1D, the NOD mouse, viral infection at different ages may either accelerate or delay disease depending on the age of infection and the type of virus. Viral infection may affect the progression of T1D via multiple mechanisms: triggering inflammation, bystander activation of self-reactive T-cells, inducing a competitive immune response, or inducing a regulatory immune response. In this paper, we create mathematical models of the interaction of viral infection with T1D progression, incorporating each of these four mechanisms. Our goal is to understand how each viral mechanism interacts with the age of infection. The model predicts that each viral mechanism has a unique pattern of interaction with disease progression. Viral inflammation always accelerates disease, but the effect decreases with age of infection. Bystander activation has little effect at younger ages and actually decreases incidence at later ages while accelerating disease in mice that do get the disease. A competitive immune response to infection can decrease incidence at young ages and increase it at older ages, with the effect decreasing over time. Finally, an induced Treg response decreases incidence at any age of infection, but the effect decreases with age. Some of these patterns resemble those seen experimentally.

An introduced parasitic fly may lead to local extinction of Darwin's finch populations.

Introduced pathogens and other parasites are often implicated in host population level declines and extinctions. However, such claims are rarely supported by rigorous real-time data. Indeed, the threat of introduced parasites often goes unnoticed until after host populations have declined severely. The recent introduction of the parasitic nest fly, Philornis downsi, to the Galápagos Islands provides an opportunity to monitor the current impact of an invasive parasite on endemic land bird populations, including Darwin's finches.In this paper we present a population viability model to explore the potential long-term effect of P. downsi on Darwin's finch populations. The goal of our study was to determine whether P. downsi has the potential to drive host populations to extinction and whether management efforts are likely to be effective.Our model is based on data from five years of experimental field work documenting the effect of P. downsi on the reproductive success of medium ground finch Geospiza fortis populations on Santa Cruz Island. Under two of the three scenarios tested, the model predicted medium ground finches are at risk of extinction within the next century.However, sensitivity analyses reveal that even a modest reduction in the prevalence of the parasite could improve the stability of finch populations. We discuss the practicality of several management options aimed at achieving this goal.Synthesis and applications. Our study demonstrates the predicted high risk of local extinction of an abundant host species, the medium ground finch Geospiza fortis due to an introduced parasite, Philornis downsi. However, our study further suggests that careful management practices aimed at reducing parasite prevalence have the potential to significantly lower the risk of host species extinction.

Vital Signs: Estimated Effects of a Coordinated Approach for Action to Reduce Antibiotic-Resistant Infections in Health Care Facilities - United States.

BACKGROUND: Treatments for health care-associated infections (HAIs) caused by antibiotic-resistant bacteria and Clostridium difficile are limited, and some patients have developed untreatable infections. Evidence-supported interventions are available, but coordinated approaches to interrupt the spread of HAIs could have a greater impact on reversing the increasing incidence of these infections than independent facility-based program efforts. METHODS: Data from CDC's National Healthcare Safety Network and Emerging Infections Program were analyzed to project the number of health care-associated infections from antibiotic-resistant bacteria or C. difficile both with and without a large scale national intervention that would include interrupting transmission and improved antibiotic stewardship. As an example, the impact of reducing transmission of one antibiotic-resistant infection (carbapenem-resistant Enterobacteriaceae [CRE]) on cumulative prevalence and number of HAI transmission events within interconnected groups of health care facilities was modeled using two distinct approaches, a large scale and a smaller scale health care network. RESULTS: Immediate nationwide infection control and antibiotic stewardship interventions, over 5 years, could avert an estimated 619,000 HAIs resulting from CRE, multidrug-resistant Pseudomonas aeruginosa, invasive methicillin-resistant Staphylococcus aureus (MRSA), or C. difficile. Compared with independent efforts, a coordinated response to prevent CRE spread across a group of inter-connected health care facilities resulted in a cumulative 74% reduction in acquisitions over 5 years in a 10-facility network model, and 55% reduction over 15 years in a 102-facility network model. CONCLUSIONS: With effective action now, more than half a million antibiotic-resistant health care-associated infections could be prevented over 5 years. Models representing both large and small groups of interconnected health care facilities illustrate that a coordinated approach to interrupting transmission is more effective than historical independent facilitybased efforts. IMPLICATIONS FOR PUBLIC HEALTH: Public health-led coordinated prevention approaches have the potential to more completely address the emergence and dissemination of these antibiotic-resistant organisms and C. difficile than independent facility-based efforts.

Bilaterally asymmetric effects of quantitative trait loci (QTLs): QTLs that affect laxity in the right versus left coxofemoral (hip) joints of the dog (Canis familiaris).

In dogs hip joint laxity that can lead to degenerative joint disease (DJD) is frequent and heritable, providing a genetic model for some aspects of the human disease. We have used Portuguese water dogs (PWDs) to identify Quantitative trait loci (QTLs) that regulate laxity in the hip joint. A population of 286 PWDs, each characterized by ca. 500 molecular genetic markers, was analyzed for subluxation of the hip joint as measured by the Norberg angle, a quantitative radiographic measure of laxity. A significant directed asymmetry was observed, such that greater laxity was observed in the left than the right hip. This asymmetry was not heritable. However, the average Norberg angle was highly heritable as were the Norberg angles of either the right or left hips. After correction for pedigree effects, two QTLs were identified using the metrics of the left and right hips as separate data sets. Both are on canine chromosome 1 (CFA1), separated by about 95 Mb. One QTL, associated with the SSR marker FH2524 was significant for the left, but not the right hip. The other, associated with FH2598, was significant for the right but not the left hip. For both QTLs, some extreme phenotypes were best explained by specific interactions between haplotypes.