Building SuperModels: emerging patient avatars for use in precision and systems medicine

Digital health: trends, opportunities and challenges in medical devices, pharma and bio-technology

Digital health interventions refer to the use of digital technology and connected devices to improve health outcomes and healthcare delivery. This includes telemedicine, electronic health records, wearable devices, mobile health applications, and other forms of digital health technology. To this end, several research and developmental activities in various fields are gaining momentum. For instance, in the medical devices sector, several smart biomedical materials and medical devices that are digitally enabled are rapidly being developed and introduced into clinical settings. In the pharma and allied sectors, digital health-focused technologies are widely being used through various stages of drug development, viz. computer-aided drug design, computational modeling for predictive toxicology, and big data analytics for clinical trial management. In the biotechnology and bioengineering fields, investigations are rapidly growing focus on digital health, such as omics biology, synthetic biology, systems biology, big data and personalized medicine. Though digital health-focused innovations are expanding the horizons of health in diverse ways, here the development in the fields of medical devices, pharmaceutical technologies and biotech sectors, with emphasis on trends, opportunities and challenges are reviewed. A perspective on the use of digital health in the Indian context is also included.

Mechanistic Computational Models of Epithelial Cell Transporters-the Adorned Heroes of Pharmacokinetics

Epithelial membrane transporter kinetics portray an irrefutable role in solute transport in and out of cells. Mechanistic models are used to investigate the transport of solutes at the organ, tissue, cell or membrane scale. Here, we review the recent advancements in using computational models to investigate epithelial transport kinetics on the cell membrane. Various methods have been employed to develop transport phenomena models of solute flux across the epithelial cell membrane. Interestingly, we noted that many models used lumped parameters, such as the Michaelis-Menten kinetics, to simplify the transporter-mediated reaction term. Unfortunately, this assumption neglects transporter numbers or the fact that transport across the membrane may be affected by external cues. In contrast, more recent mechanistic transporter kinetics models account for the transporter number. By creating models closer to reality researchers can investigate the downstream effects of physical or chemical disturbances on the system. Evidently, there is a need to increase the complexity of mechanistic models investigating the solute flux across a membrane to gain more knowledge of transporter-solute interactions by assigning individual parameter values to the transporter kinetics and capturing their dependence on each other. This change results in better pharmacokinetic predictions in larger scale platforms. More reliable and efficient model predictions can be made by creating mechanistic computational models coupled with dedicated in vitro experiments. It is also vital to foster collaborative efforts among transporter kinetics researchers in the modeling, material science and biological fields.

Lessons from Hippocrates: Time to Change the Cancer Paradigm

The ultimate goal of all medical activity is to restore patients to a state of complete physical, mental, and social wellbeing. In cancer, it is assumed that this can only be obtained through the complete eradication of the tumor burden. So far, this strategy has led to a substantial improvement in cancer survival rates. Despite this, more than 9 million people die from cancer every year. Therefore, we need to accept that our current cancer treatment paradigm is obsolete and must be changed. The new paradigm should reflect that cancer is a systemic disease, which affects an individual patient living in a particular social reality, rather than an invading organism or a mere cluster of mutated cells that need to be eradicated. This Hippocratic holistic view will ultimately lead to an improvement in health and wellbeing in cancer patients. They deserve nothing less.

AVATAR: Analysis for Visual Acuity Prediction After Eye Interventional Radiotherapy

AIM

The aim of this study was to detect clinical factors predictive of loss of visual acuity after treatment in order to develop a predictive model to help identify patients at risk of visual loss.

PATIENTS AND METHODS

This was a retrospective review of patients who underwent interventional radiotherapy (brachytherapy) with 106Ru plaque for primary uveal melanoma. A predictive nomogram for visual acuity loss at 3 years from treatment was developed.

RESULTS

A total of 152 patients were selected for the study. The actuarial probability of conservation of 20/40 vision or better was 0.74 at 1 year, 0.59 at 3 years, and 0.54 at 5 years after treatment. Factors positively correlated with loss of visual acuity included: age at start of treatment (p=0.004) and longitudinal basal diameter (p=0.057), while distance of the posterior margin of the tumor from the foveola was inversely correlated (p=0.0007).

CONCLUSION

We identified risk factors affecting visual function and developed a predictive model and decision support tool (AVATAR nomogram).

Poetic Science: Bidirectional Reflection in Science and Medicine

The arts are making their mark in science, technology, engineering, arts, and mathematics/medicine (STEAM). Integrating creative expression-poetry and other visual and performing arts-can help clinicians, scientists, and others use familiar social constructs to embody science and medicine, in what may be termed poetic science. Poetic science imbues bidirectional reflections of science and medicine on the clinician or scientist or other inquisitor, creatively engaging the learner's brain cells as mirrors. This ultimately leads to a subjective perspective on the understanding or the proposition of underlying principles. Such an approach is encouraged here with poignant examples that can be accessed publicly online and used widely by readers, teachers, learners, clinicians, scientists, students, and others.

Functionalized Anatomical Models for Computational Life Sciences

The advent of detailed computational anatomical models has opened new avenues for computational life sciences (CLS). To date, static models representing the anatomical environment have been used in many applications but are insufficient when the dynamics of the body prevents separation of anatomical geometrical variability from physics and physiology. Obvious examples include the assessment of thermal risks in magnetic resonance imaging and planning for radiofrequency and acoustic cancer treatment, where posture and physiology-related changes in shape (e.g., breathing) or tissue behavior (e.g., thermoregulation) affect the impact. Advanced functionalized anatomical models can overcome these limitations and dramatically broaden the applicability of CLS in basic research, the development of novel devices/therapies, and the assessment of their safety and efficacy. Various forms of functionalization are discussed in this paper: (i) shape parametrization (e.g., heartbeat, population variability), (ii) physical property distributions (e.g., image-based inhomogeneity), (iii) physiological dynamics (e.g., tissue and organ behavior), and (iv) integration of simulation/measurement data (e.g., exposure conditions, “validation evidence” supporting model tuning and validation). Although current model functionalization may only represent a small part of the physiology, it already facilitates the next level of realism by (i) driving consistency among anatomy and different functionalization layers and highlighting dependencies, (ii) enabling third-party use of validated functionalization layers as established simulation tools, and (iii) therefore facilitating their application as building blocks in network or multi-scale computational models. Integration in functionalized anatomical models thus leverages and potentiates the value of sub-models and simulation/measurement data toward ever-increasing simulation realism. In our o²S²PARC platform, we propose to expand the concept of functionalized anatomical models to establish an integration and sharing service for heterogeneous computational models, ranging from the molecular to the organ level. The objective of o²S²PARC is to integrate all models developed within the National Institutes of Health SPARC initiative in a unified anatomical and computational environment, to study the role of the peripheral nervous system in controlling organ physiology. The functionalization concept, as outlined for the o²S²PARC platform, could form the basis for many other application areas of CLS. The relationship to other ongoing initiatives, such as the Physiome Project, is also presented.

A P5 Approach to m-Health: Design Suggestions for Advanced Mobile Health Technology

In recent years, technology has been developed as an important resource for health care management, especially in regard to chronic conditions. In the broad field of eHealth, mobile technology (mHealth) is increasingly used to empower patients not only in disease management but also in the achievement of positive experiences and experiential growth. mHealth tools are considered powerful because, unlike more traditional Internet-based tools, they allow patients to be continuously monitored and followed by their own mobile devices and to have continual access to resources (e.g., mobile apps or functions) supporting health care management activities. However, the literature has shown that, in many cases, such technology not accepted and/or adopted in the long term by its users. To address this issue, this article reviews the main factors influencing mHealth technology acceptance/adoption in health care. Finally, based on the main aspects emerging from the review, we propose an innovative approach to mHealth design and implementation, namely P5 mHealth. Relying on the P5 approach to medicine and health care, this approach provides design suggestions to address mHealth adoption issues already at the initial stages of development of the technologies.

The coming era of precision medicine for intensive care

Recent advances in technology and better understanding of mechanisms underlying disease are beginning to enable us to better characterize critically ill patients. Instead of using nonspecific syndromic groupings, such as sepsis or acute respiratory distress syndrome, we can now classify individual patients according to various specific characteristics, such as immune status. This "personalized" medicine approach will enable us to distinguish patients who have similar clinical presentations but different cellular and molecular responses that will influence their need for and responses (both negative and positive) to specific treatments. Treatments will be able to be chosen more accurately for each patient, resulting in more rapid institution of appropriate, effective therapy. We will also increasingly be able to conduct trials in groups of patients specifically selected as being most likely to respond to the intervention in question. This has already begun with, for example, some new interventions being tested only in patients with coagulopathy or immunosuppressive patterns. Ultimately, as we embrace this era of precision medicine, we may be able to offer precision therapies specifically designed to target the molecular set-up of an individual patient, as has begun to be done in cancer therapeutics.

Behavioral Phenotyping Assays for Genetic Mouse Models of Neurodevelopmental, Neurodegenerative, and Psychiatric Disorders

Animal models offer heuristic research tools to understand the causes of human diseases and to identify potential treatments. With rapidly evolving genetic engineering technologies, mutations identified in a human disorder can be generated in the mouse genome. Phenotypic outcomes of the mutation are then explicated to confirm hypotheses about causes and to discover effective therapeutics. Most neurodevelopmental, neurodegenerative, and psychiatric disorders are diagnosed primarily by their prominent behavioral symptoms. Mouse behavioral assays analogous to the human symptoms have been developed to analyze the consequences of mutations and to evaluate proposed therapeutics preclinically. Here we describe the range of mouse behavioral tests available in the established behavioral neuroscience literature, along with examples of their translational applications. Concepts presented have been successfully used in other species, including flies, worms, fish, rats, pigs, and nonhuman primates. Identical strategies can be employed to test hypotheses about environmental causes and gene × environment interactions.