Precision medicine: an opportunity for a paradigm shift in veterinary medicine

Data Governance and Distribution of Biobank: A Case from a Chinese Cancer Hospital

Objectives: To facilitate the regionalization, specialization, and digitization of biobanks, three issues regarding data collection and application must be addressed (1) integration and distribution of data governance, (2) efficiency and efficacy of data governance, and (3) sustainability of data governance. Methods: We collaborated with stakeholders to identify priorities and assess infrastructure needs through the continuous evaluation and analysis of projects. We developed data management solutions, catalogs, and data models to optimize and support data collection, distribution, and application. Furthermore, ontologies were used to facilitate data integration from multiple sources, and Minimum Information About BIobank Data Sharing (MIABIS) was defined as accessible to all patients. To enhance data integrity, we conducted retrospective and prospective follow-up studies. Results: We completed infrastructure upgrades to match technical solutions and research demands. An information management software with six primary functional divisions was developed for data governance. We optimized the database structure and changed the biospecimen accumulation model from biospecimen-based to patient-centered and service-oriented. Subsequently, we specified 85 attributes of MIABIS to describe the biobank contents. A dual-pillar approach was adopted to expand the biobank's data in collaboration with other institutions, and MIABIS served as a bridge for both vertical and horizontal networks. From 2003 to 2021, we collected a total of 156,997 patient biospecimens/data from 20 cancer types, matching 53,113 cases from follow-up surveys. In addition, we supplied more than 40,000 biospecimens/data points for above 300 scientific research projects. Conclusions: An appropriate information platform for a biobank is fundamental to data collection, distribution, and application, particularly in the context of data-intensive research. We implemented a standardized scientific data structure to fulfill the research requirements. The sustainable development of a biobank depends on a scientific, standardized, and service-oriented data governance approach, along with the efficient utilization of emerging technologies.

Precision Medicine in Veterinary Science

Precision medicine focuses on the clinical management of the individual patient, not on population-based findings. Successes from human precision medicine inform veterinary oncology. Early evidence of success for canines shows how precision medicine can be integrated into practice. Decreasing genomic profiling costs will allow increased utilization and subsequent improvement of knowledge base from which to make better informed decisions. Utility of precision medicine in canine oncology will only increase for improved cancer characterization, enhanced therapy selection, and overall more successful management of canine cancer. As such, practitioners are called to interpret and leverage precision medicine reports for their patients.

The MARS PETCARE BIOBANK protocol: establishing a longitudinal study of health and disease in dogs and cats

BACKGROUND

The veterinary care of cats and dogs is increasingly embracing innovations first applied to human health, including an increased emphasis on preventative care and precision medicine. Large scale human population biobanks have advanced research in these areas; however, few have been established in veterinary medicine. The MARS PETCARE BIOBANK™ (MPB) is a prospective study that aims to build a longitudinal bank of biological samples, with paired medical and lifestyle data, from 20,000 initially healthy cats and dogs (10,000 / species), recruited through veterinary hospitals over a ten-year period. Here, we describe the MPB protocol and discuss its potential as a platform to increase understanding of why and how diseases develop and how to advance personalised veterinary healthcare.

METHODS

At regular intervals, extensive diet, health and lifestyle information, electronic medical records, clinicopathology and activity data are collected, genotypes, whole genome sequences and faecal metagenomes analysed, and blood, plasma, serum, and faecal samples stored for future research.

DISCUSSION

Proposed areas for research include the early detection and progression of age-related disease, risk factors for common conditions, the influence of the microbiome on health and disease and, through genome wide association studies, the identification of candidate loci for disease associated genetic variants. Genomic data will be open access and research proposals for access to data and samples will be considered. Over the coming years, the MPB will provide the longitudinal data and systematically collected biological samples required to generate important insights into companion animal health, identifying biomarkers of disease, supporting earlier identification of risk, and enabling individually tailored interventions to manage disease.

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case

Smart cities and digital public health are closely related. Managing digital transformation in urbanization and living spaces is challenging. It is critical to prioritize the emotional and physical health and well-being of humans and their animals in the dynamic and ever-changing environment they share. Human-animal bonds are continuous as they live together or share urban spaces and have a mutual impact on each other's health as well as the surrounding environment. In addition, sensors embedded in the Internet of Things are everywhere in smart cities. They monitor events and provide appropriate responses. In this regard, accident and emergency informatics (A&EI) offers tools to identify and manage overtime hazards and disruptive events. Such manifold focuses fit with One Digital Health (ODH), which aims to transform health ecosystems with digital technology by proposing a comprehensive framework to manage data and support health-oriented policies. We showed and discussed how, by developing the concept of ODH intervention, the ODH framework can support the comprehensive monitoring and analysis of daily life events of humans and animals in technologically integrated environments such as smart homes and smart cities. We developed an ODH intervention use case in which A&EI mechanisms run in the background. The ODH framework structures the related data collection and analysis to enhance the understanding of human, animal, and environment interactions and associated outcomes. The use case looks at the daily journey of Tracy, a healthy woman aged 27 years, and her dog Mego. Using medical Internet of Things, their activities are continuously monitored and analyzed to prevent or manage any kind of health-related abnormality. We reported and commented on an ODH intervention as an example of a real-life ODH implementation. We gave the reader examples of a "how-to" analysis of Tracy and Mego's daily life activities as part of a timely implementation of the ODH framework. For each activity, relationships to the ODH dimensions were scored, and relevant technical fields were evaluated in light of the Findable, Accessible, Interoperable, and Reusable principles. This "how-to" can be used as a template for further analyses. An ODH intervention is based on Findable, Accessible, Interoperable, and Reusable data and real-time processing for global health monitoring, emergency management, and research. The data should be collected and analyzed continuously in a spatial-temporal domain to detect changes in behavior, trends, and emergencies. The information periodically gathered should serve human, animal, and environmental health interventions by providing professionals and caregivers with inputs and "how-to's" to improve health, welfare, and risk prevention at the individual and population levels. Thus, ODH complementarily combined with A&EI is meant to enhance policies and systems and modernize emergency management.

Banking on the Last Gift: Cornell's Signature Program of Postmortem Tissue Procurement

High-quality, well-annotated, healthy tissue specimens are crucial to the success of basic and translational research, but often difficult to procure. Postmortem (PM) tissue collections provide the opportunity to collect these healthy biospecimens. PM procurement programs led by biobanks can further contribute by providing researchers with rare biospecimens collected with short postmortem intervals (PMI) in controlled environments. To support biomedical and translational research, the Cornell Veterinary Biobank (CVB), an ISO 20387 accredited core resource at the Cornell University College of Veterinary Medicine, has performed PM tissue collections from research and privately owned animals since 2013. The CVB PM collection team, consisting of a board-certified veterinary pathologist, a licensed veterinary technician collection specialist, and a data capture specialist, performs rapid tissue collections during controlled warm necropsies, with an accepted PMI of ≤2 hours and a target PMI of ≤1 hour. A retrospective analysis of PM collections between 2013 and 2020 was completed, consisting of 4077 aliquots of 1582 biospecimens from 69 donors (48 canine, 16 feline, and 5 equine). An average of 22.93 biospecimens per donor were collected (range: 1-49). The average PMI for standard collections was 43.48 ± 2.30 minutes, starting on average 20.81 ± 1.61 minutes after time of death. Thus far, the CVB has a favorable utilization rate, with 414 aliquots (10.15%) from 350 specimens (20.12%) and 45 animals (65.22%) distributed to researchers. The success of the CVB PM tissue biobanking program, collecting high-quality biospecimens with short PMIs, was due to support from veterinary pathologists, the competence of CVB personnel, and the continuous evolution of methods within a quality management system. Improvement of PM tissue collection programs in biobanks, with standardized practices for all processes and specialized personnel, can enhance the quality and increase utilization of its biospecimens and associated data.

Artificial Intelligence and Precision Medicine: A New Frontier for the Treatment of Brain Tumors

Brain tumors are a widespread and serious neurological phenomenon that can be life- threatening. The computing field has allowed for the development of artificial intelligence (AI), which can mimic the neural network of the human brain. One use of this technology has been to help researchers capture hidden, high-dimensional images of brain tumors. These images can provide new insights into the nature of brain tumors and help to improve treatment options. AI and precision medicine (PM) are converging to revolutionize healthcare. AI has the potential to improve cancer imaging interpretation in several ways, including more accurate tumor genotyping, more precise delineation of tumor volume, and better prediction of clinical outcomes. AI-assisted brain surgery can be an effective and safe option for treating brain tumors. This review discusses various AI and PM techniques that can be used in brain tumor treatment. These new techniques for the treatment of brain tumors, i.e., genomic profiling, microRNA panels, quantitative imaging, and radiomics, hold great promise for the future. However, there are challenges that must be overcome for these technologies to reach their full potential and improve healthcare.

Genomic Medicine in Periodontal Disease: Old Issue, New Insights

Genetic variability is the main cause of phenotypic variation. Some variants may be associated with several diseases and can be used as risk biomarkers, identifying animals with higher susceptibility to develop the pathology. Genomic medicine uses this genetic information for risk calculation, clinical diagnosis and prognosis, allowing the implementation of more effective preventive strategies and/or personalized therapies. Periodontal disease (PD) is the inflammation of the periodontium induced mainly by bacterial plaque and is the leading cause of tooth loss. Microbial factors are responsible for the PD initiation; however, several studies support the genetic influence on the PD progression. The main purpose of the present publication is to highlight the main steps involved in the genomic medicine applied to veterinary patients, describing the flowchart from the characterization of the genetic variants to the identification of potential associations with specific clinical data. After investigating which genes might potentially be implicated in canine PD, the RANK gene, involved in the regulation of osteoclastogenesis, was selected to illustrate this approach. A case-control study was performed using DNA samples from a population of 90 dogs – 50 being healthy and 40 with PD. This analysis allowed for the discovery of four new intronic variations that were banked in GenBank (g.85A>G, g.151G>T, g.268A>G and g.492T>C). The results of this study are not intended to be applied exclusively to PD. On the contrary, this genetic information is intended to be used by other researchers as a foundation for the development of multiple applications in the veterinary clinical field.

Constructing and analysing dynamic models with modelbase v1.2.3: a software update

BACKGROUND

Computational mathematical models of biological and biomedical systems have been successfully applied to advance our understanding of various regulatory processes, metabolic fluxes, effects of drug therapies, and disease evolution and transmission. Unfortunately, despite community efforts leading to the development of SBML and the BioModels database, many published models have not been fully exploited, largely due to a lack of proper documentation or the dependence on proprietary software. To facilitate the reuse and further development of systems biology and systems medicine models, an open-source toolbox that makes the overall process of model construction more consistent, understandable, transparent, and reproducible is desired.

RESULTS AND DISCUSSION

We provide an update on the development of modelbase, a free, expandable Python package for constructing and analysing ordinary differential equation-based mathematical models of dynamic systems. It provides intuitive and unified methods to construct and solve these systems. Significantly expanded visualisation methods allow for convenient analysis of the structural and dynamic properties of models. After specifying reaction stoichiometries and rate equations modelbase can automatically assemble the associated system of differential equations. A newly provided library of common kinetic rate laws reduces the repetitiveness of the computer programming code. modelbase is also fully compatible with SBML. Previous versions provided functions for the automatic construction of networks for isotope labelling studies. Now, using user-provided label maps, modelbase v1.2.3 streamlines the expansion of classic models to their isotope-specific versions. Finally, the library of previously published models implemented in modelbase is growing continuously. Ranging from photosynthesis to tumour cell growth to viral infection evolution, all these models are now available in a transparent, reusable and unified format through modelbase.

CONCLUSION

With this new Python software package, which is written in currently one of the most popular programming languages, the user can develop new models and actively profit from the work of others. modelbase enables reproducing and replicating models in a consistent, tractable and expandable manner. Moreover, the expansion of models to their isotopic label-specific versions enables simulating label propagation, thus providing quantitative information regarding network topology and metabolic fluxes.

A Biobank's Journey: Implementation of a Quality Management System and Accreditation to ISO 20387

Biobanks play an integral role in research and precision medicine by acquiring, processing, storing, and distributing high-quality, clinically annotated biological material. Compliance with biobanking standards and the implementation of quality management systems (QMS) can improve the quality of the biological material and associated data (BMaD). By undergoing third-party assessments, biobanks can demonstrate compliance to these standards and instill confidence in their users. In the 8 months following the publication of the International Organization for Standardization (ISO) 20387:2018 General Requirements for Biobanking standard, the Cornell Veterinary Biobank (CVB) became compliant with the standard requirements, including developing and implementing a QMS. This was achieved through the documentation of all biobanking processes, demonstration of personnel competence, the stringent control of documents and records, and ongoing evaluation of processes and the QMS. Procedures describing the control of documents and records were implemented first to provide a foundation on which to build the QMS, followed by procedures for documenting the identification of risks and opportunities, improvements, and corrective actions following nonconforming outputs. Internal audit and management review programs were developed to verify QMS performance and to monitor quality objectives. Procedures for the governance and management of the biobank were developed, including the following: organizational structure; confidentiality and impartiality policies; facility and equipment maintenance, calibration, and monitoring; personnel training and competency; and evaluation of external providers. All processes on scope were described, along with the validation and verification of methods, to ensure the fitness-for-purpose of the BMaD and the reproducibility of biobanking processes. Training sessions were held during implementation of the QMS to ensure all personnel would conform to the procedures. In April 2019, the CVB underwent third-party assessment by the American Association of Laboratory Accreditation (A2LA) and became the first biobank in the world to receive accreditation to ISO 20387:2018.

Nanotechnology and Animal Health

Nanotechnology has been a rapidly expanding area of research with huge potential in many sectors, including animal healthcare. It promises to revolutionize drug and vaccine delivery, diagnostics, and theranostics, which has become an important tool in personalized medicine by integrating therapeutics and diagnostics. Nanotechnology has also been used successfully in animal nutrition. In this review, the application of nanotechnology in animal health will be reviewed with its pros and cons.

Precision/Genomic Medicine for Domestic Cats

The era of Precision / Genomic Medicine has arrived and can improve the veterinary healthcare of companion animals. The goal of Precision / Genomic Medicine is to use an individual's DNA signature / profile to tailor their treatments of their specific health problems. Whole genome sequencing is now a cost-effective diagnostic tool, leading to the discovery of DNA variants associated with health outcomes. These DNA variants become genetic tests and can readily be applied to future cases of individuals with similar symptoms. This article addresses the current state of Precision Medicine in domestic cats and the implications for veterinary care.

Towards the Delivery of Precision Veterinary Cancer Medicine

We introduce a next phase in the evolution of medicine affecting human and veterinary patients. This evolution, genomic cancer medicine (Pmed), involves expansion of genomic and molecular biology into clinical medicine. The implementation of these new technologies has already begun and is a commercial reality. We introduce the underpinnings for this evolution, and focus on application in complex disease states. Pet owners have begun requesting Pmed technologies. To meet this demand, it is important to be aware of the opportunities and obstacles associated with available Pmed offerings as well as the current state of the field.