From pathogenesis to precision medicine: Targeting immune imbalance in multiple sclerosis.

Precision Medicine: The new era in medicine

Precision Medicine in Inflammatory Bowel Diseases: Challenges and Considerations for the Path Forward

The promise of precision medicine in autism

Precision medicine in nonalcoholic fatty liver disease.

(1) Background: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce. MS sherpa is an eHealth intervention with digital biomarkers, aimed at monitoring symptom progression and disease activity. To show the added value of digital biomarker–based eHealth interventions to the MS care path, an early Health Technology Assessment (eHTA) was performed, with MS sherpa as an example, to assess the potential impact on treatment switches. (2) Methods: The eHTA was performed according to the Dutch guidelines for health economic evaluations. A decision analytic MS model was used to estimate the costs and benefits of MS standard care with and without use of MS sherpa, expressed in incremental cost-effectiveness ratios (ICERs) from both societal and health care perspectives. The efficacy of MS sherpa on early detection of active disease and the initiation of a treatment switch were modeled for a range of assumed efficacy (5%, 10%, 15%, 20%). (3) Results: From a societal perspective, for the efficacy of 15% or 20%, MS sherpa became dominant, which means cost-saving compared to the standard of care. MS sherpa is cost-effective in the 5% and 10% scenarios (ICERs EUR 14,535 and EUR 4069, respectively). From the health care perspective, all scenarios were cost-effective. Sensitivity analysis showed that increasing the efficacy of MS sherpa in detecting active disease early leading to treatment switches be the most impactful factor in the MS model. (4) Conclusions: The results indicate the potential of eHealth interventions to be cost-effective or even cost-saving in the MS care path. As such, digital biomarker–based eHealth interventions, like MS sherpa, are promising cost-effective solutions in optimizing MS disease management for people with MS, by detecting active disease early and helping neurologists in decisions on treatment switch.

1551 Background: Pediatric and adult patients with rare, relapsed, or refractory cancers often have few treatment options. Precision medicine approaches are often the first strategy used to identify salvage therapy options when standard treatments fail. Despite the significant clinical benefit to advanced cancer patients, multiple genomics precision medicine trials have revealed important constraints for patients that lack treatments matched to mutations or biomarkers and have highlighted challenges in drug accessibility associated with novel targeted therapies identified through genomics precision medicine. Current clinical findings from large-scale studies demonstrate ~10% of cancer patients receive clinical benefit from genomics-guided therapies - in part due to limited insight into the complex relationship between tumor molecular characteristics and patient response. Methods: We implemented a functional precision medicine (FPM) approach combining genomic tumor profiling with high-throughput drug sensitivity testing (DST) of FDA-approved agents on patient-derived tumor cells to identify treatment options when standard-of-care is exhausted. Clinical utility and benefit of this program was investigated via a clinical trial (NCT03860376) at Nicklaus Children’s Hospital in Miami, FL. Results: We were returned DST data on 21 of 24 patients DST (median = 102 agents per sample) and genomic profiling on 20 of 24 patients. DST turnaround time was significantly below the 14 days required for clinical use (median = 10 days, p = 0.0012). FPM recommendations were returned to 19 (76%) patients, of which 14 patients underwent therapeutic intervention. Six patients received FPM-guided treatments, and five (83%) patients experienced a >1.3-fold improved progression-free survival over their previous therapy, significantly above the rate from physician’s choice (p = 0.0104). We subsequently opened pan-cancer FPM clinical studies for adults (n = 36 patients) and children (n = 65 patients). A key objective in these trials is optimizing our DST protocol for tissue samples of various sizes. Here, we report preliminary efforts to optimize our DST approach for tissue samples from resections, core biopsies, and fine-needle biopsies from primary and metastatic lesions. Conclusions: The findings from our feasibility study illustrate the potential for FPM to positively impact clinical care for pediatric/adolescent patients with relapsed/refractory cancers, and have supported initiation of currently enrolling clinical studies. An NIMHD-funded expansion cohort now enrolling at Nicklaus Children’s Hospital (NCT05857969, n = 65 patients), and a rare/relapsed/refractory adult patient cohort at Cleveland Clinic Florida (NCT06024603, n = 36 patients). These studies aim to further investigate the impact on clinical outcomes through the use of FPM to recommend treatment options. Clinical trial information: NCT06024603 , NCT05857969 , NCT04956198 , NCT03860376 .

For incurable diseases, such as multiple sclerosis (MS), the prevention of progression and the preservation of quality of life play a crucial role over the entire therapy period. In MS, patients tend to become ill at a younger age and are so variable in terms of their disease course that there is no standard therapy. Therefore, it is necessary to enable a therapy that is as personalized as possible and to respond promptly to any changes, whether with noticeable symptoms or symptomless. Here, measurable parameters of biological processes can be used, which provide good information with regard to prognostic and diagnostic aspects, disease activity and response to therapy, so-called biomarkers Increasing digitalization and the availability of easy-to-use devices and technology also enable healthcare professionals to use a new class of digital biomarkers—digital health technologies—to explain, influence and/or predict health-related outcomes. The technology and devices from which these digital biomarkers stem are quite broad, and range from wearables that collect patients’ activity during digitalized functional tests (e.g., the Multiple Sclerosis Performance Test, dual-tasking performance and speech) to digitalized diagnostic procedures (e.g., optical coherence tomography) and software-supported magnetic resonance imaging evaluation. These technologies offer a timesaving way to collect valuable data on a regular basis over a long period of time, not only once or twice a year during patients’ routine visit at the clinic. Therefore, they lead to real-life data acquisition, closer patient monitoring and thus a patient dataset useful for precision medicine. Despite the great benefit of such increasing digitalization, for now, the path to implementing digital biomarkers is widely unknown or inconsistent. Challenges around validation, infrastructure, evidence generation, consistent data collection and analysis still persist. In this narrative review, we explore existing and future opportunities to capture clinical digital biomarkers in the care of people with MS, which may lead to a digital twin of the patient. To do this, we searched published papers for existing opportunities to capture clinical digital biomarkers for different functional systems in the context of MS, and also gathered perspectives on digital biomarkers under development or already existing as a research approach.

Multiple Sclerosis (MS) is a chronic, autoimmune, demyelinating disease of the central nervous system. It is a complex and heterogeneous disease, and its pathogenesis is still not completely understood. Precision medicine, which involves the use of advanced technologies such as genomics, proteomics, metabolomics, and imaging to identify specific biomarkers and disease subtypes, is a promising approach to the management of multiple sclerosis. Precision medicine in MS includes the development of targeted therapies that aim to modulate specific immune pathways involved in MS pathogenesis. This review article aims to provide an overview of the current status and future directions of precision medicine in MS. The article discusses the importance of precision diagnostics in MS, including the identification of biomarkers and imaging techniques for MS, as well as the challenges and opportunities of personalized treatment in MS. Targeted therapies in MS are also discussed, including the challenges of developing and implementing these therapies. The article highlights the potential of combination therapies in MS, and the role of AI and ML in improving biomarker identification. The challenges of implementing precision medicine in clinical practice are also addressed, including the standardization of diagnostic criteria and treatment guidelines, and the ethical and legal considerations of personalized treatment. Overall, precision medicine represents a promising approach to the management of MS, with the potential to improve diagnosis, prognosis, and treatment outcomes. However, the implementation of precision medicine in MS clinical practice requires addressing several challenges, including the standardization of diagnostic criteria and treatment guidelines, and the development of affordable and accessible technologies and therapies. With continued research and advances in technology, precision medicine has the potential to transform the field of MS research and clinical practice.

Madam, I am writing to discuss the rapidly evolving field of precision medicine (PM), an exciting and highly relevant topic that has garnered increasing attention in Pakistan in recent years. PM is an approach that considers individual differences in genetics, environment, and lifestyle to tailor medical treatment for each patient, rather than relying on a one-size-fits-all approach1. There are several potential benefits of PM for patients in Pakistan. By tailoring treatments to individual needs, PM can lead to more effective treatments and improved patient outcomes. For instance, a recent study found that PM approaches resulted in better outcomes for patients with head and neck cancer2. We can also see big applications of PM in diabetes, which is quite a common disease in Pakistan. PM can revolutionize diabetes care by utilizing genetics to inform diagnosis, therapy, drug dosage, monitoring, and treatment of complications, while it may not yet be widely used, it is expected to become a routine aspect of diabetes care in the near future3. In addition, PM can reduce healthcare costs in the long run by avoiding unnecessary treatments and hospitalizations4. Despite these benefits, the adoption of PM in Pakistan is still in its early stages. There is progress to be made in implementing PM in the country, and several challenges must be overcome such as investment in the infrastructure, training, research, and development required to make PM more widely available and affordable. One big issue regarding PM is its role in the public health domain, as public health experts have expressed doubts about prioritizing individualized approaches for treating sick individuals instead of population-based prevention programs that consider broader factors affecting health like behavior, environment, and society5. But populations managed by PM contribute to a vast amount of data with their unique genetic and socioeconomic traits. Through the analysis of this data using more modern technology, such as machine learning, high risk people may be predicted, which is a game-changer for public health6. To achieve this reality of PM, there is a need to invest in infrastructure, training, and research in this field. In conclusion, PM has the potential to revolutionize healthcare by providing personalized treatment options based on individual factors such as genetics and lifestyle. While there are challenges to implementing PM in LMICs, the field is advancing rapidly, and ongoing research is providing hope for the bright future of personalized medicine in Pakistan.

Multiple sclerosis (MS) is the most common inflammatory demyelinating disease in the central nervous system. It is one of the major causes of disability in young adults. Early diagnosis and treatment of this disease could decrease later disability and additional costs. In this cross-sectional analytical study, a total of 351 patients were selected from among the multiple sclerosis patients that went to MS clinic or neurologic clinic in 1990-2016. Data were collected and analysed by SPSS v16. This study was conducted on 82.6% females and 17.4% males. Family history of MS was positive in 12.8% of cases. Mean time of onset of symptoms till first medical visit was 3.25months. Mean time from first medical visit to diagnosis was 14.98months. Mean time from onset of symptoms till diagnosis was 18.01months and the mean time from onset of symptoms till initiation of treatment was 18.73months. Also, 29.3% of cases had delay in first medical visit and 42.2% of cases had delay in diagnosis of MS more than 6weeks from first medical visit. Overall, delay in first medical visit and diagnosis of MS has decreased over the years. However, there is still delay in diagnosis of MS. Factors associated with delay are low education, male gender, living in rural areas, primary progressive MS, age at MS diagnosis and first clinical symptoms.

Molecular Imaging and Precision Medicine in Dementia and Movement Disorders

Higher frequency of Human herpesvirus-6 (HHV-6) viral DNA simultaneously with low frequency of Epstein-Barr virus (EBV) viral DNA in a cohort of multiple sclerosis patients from Rio de Janeiro, Brazil.

Precision Medicine (PM) is an innovative approach that, by relying on large populations’ datasets, patients’ genetics and characteristics, and advanced technologies, aims at improving risk stratification and at identifying patient-specific management through targeted diagnostic and therapeutic strategies. Cardiac channelopathies are being progressively involved in the evolution brought by PM and some of them are benefiting from these novel approaches, especially the long QT syndrome. Here, we have explored the main layers that should be considered when developing a PM approach for cardiac channelopathies, with a focus on modern in vitro strategies based on patient-specific human-induced pluripotent stem cells and on in silico models. PM is where scientists and clinicians must meet and integrate their expertise to improve medical care in an innovative way but without losing common sense. We have indeed tried to provide the cardiologist’s point of view by comparing state-of-the-art techniques and approaches, including revolutionary discoveries, to current practice. This point matters because the new approaches may, or may not, exceed the efficacy and safety of established therapies. Thus, our own eagerness to implement the most recent translational strategies for cardiac channelopathies must be tempered by an objective assessment to verify whether the PM approaches are indeed making a difference for the patients. We believe that PM may shape the diagnosis and treatment of cardiac channelopathies for years to come. Nonetheless, its potential superiority over standard therapies should be constantly monitored and assessed before translating intellectually rewarding new discoveries into clinical practice.

Precision medicine focuses on understanding the heterogeneity of cancer at the individual patient level. Cancer may develop from multiple genetic mutations, and each cancer cell might have its own genetic makeup. The individualized features of cancer contribute to the challenge of developing an effective chemotherapy regimen. The advances in synthetic biology and single-cell RNA sequencing technologies have made it possible to longitudinally track the dynamic changes of gene expression in cancer cells during chemotherapy. This understanding can be translated into developing individualized chemotherapy regimens. Precision medicine can be used to monitor the efficacy of chemotherapy and predict the likelihood of chemoresistance. Currently, the response of cancer to chemotherapy is mostly assessed through a single-endpoint measurement using imaging technologies such as computed tomography. This approach is limited because it is not sensitive to tumor dormancy and cancer heterogeneity. The recent advances in high-throughput sequencing technologies now enable the detection of residual cancer cells and tumor dormancy. This information can be used to monitor the efficacy of chemotherapy and predict the likelihood of chemoresistance. Precision medicine can be used to identify genetic variations that may influence how a patient will respond to a particular drug. The information so obtained can then be used to help the healthcare provider choose the most appropriate chemotherapy regimen for each patient. In addition, precision medicine can be used to predict which patients may be more likely to experience serious side effects from chemotherapy, and can help to guide preventive strategies, such as dose adjustments or pre-treatment with other medications. Although precision medicine is increasingly being used to help tailor cancer chemotherapy to the individual patient to maximize the efficacy of the treatment and minimize side effects, it holds great promise in cancer chemotherapy only when backed by strong evidence. To fully realize the potential of precision medicine, it is important to consider the following issues. First, precision medicine approaches need to be integrated into clinical decision-making. Second, there is a need to develop robust and reliable biomarkers for precision medicine. Third, it is important to develop a comprehensive understanding of the heterogeneity of cancer. Fourth, it is necessary to develop efficient computational methods for analyzing high-throughput sequencing data. Finally, it is important to establish a robust infrastructure for storing and sharing precision medicine data Sami Siraj Editor-In-Chief Precision Medicine Communications

Background: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease that is associated with multiple environmental factors. Among suspected susceptibility events, studies have questioned the potential role of overt viral and bacterial infections, including the Epstein Bar virus (EBV) and human endogenous retroviruses (HERV). Furthermore, the fast development of immunomodulatory therapies further questions the efficacy of the standard immunization policies in MS patients. Topics reviewed: This narrative review will discuss the potential interplay between viral and bacterial infections and their treatment on MS susceptibility and disease progression. In addition, the review specifically discusses the interactions between MS pathophysiology and vaccination for hepatitis B, influenza, human papillomavirus, diphtheria, pertussis, and tetanus (DTP), and Bacillus Calmette-Guerin (BCG). Data regarding potential interaction between MS disease modifying treatment (DMT) and vaccine effectiveness is also reviewed. Moreover, HERV-targeted therapies such as GNbAC1 (temelimab), EBV-based vaccines for treatment of MS, and the current state regarding the development of T-cell and DNA vaccination are discussed. Lastly, a reviewing commentary on the recent 2019 American Academy of Neurology (AAN) practice recommendations regarding immunization and vaccine-preventable infections in the settings of MS is provided. Conclusion: There is currently no sufficient evidence to support associations between standard vaccination policies and increased risk of MS. MS patients treated with immunomodulatory therapies may have a lower benefit from viral and bacterial vaccination. Despite their historical underperformance, new efforts in creating MS-based vaccines are currently ongoing. MS vaccination programs follow the set back and slow recovery which is widely seen in other fields of medicine.