A Unified Survey of Treatment Effect Heterogeneity Modelling and Uplift Modelling

A central question in many fields of scientific research is to determine how an outcome is affected by an action, i.e., to estimate the causal effect or treatment effect of an action. In recent years, in areas such as personalised healthcare, sociology, and online marketing, a need has emerged to estimate heterogeneous treatment effects with respect to individuals of different characteristics. To meet this need, two major approaches have been taken: treatment effect heterogeneity modelling and uplifting modelling. Researchers and practitioners in different communities have developed algorithms based on these approaches to estimate the heterogeneous treatment effects. In this article, we present a unified view of these two seemingly disconnected yet closely related approaches under the potential outcome framework. We provide a structured survey of existing methods following either of the two approaches, emphasising their inherent connections and using unified notation to facilitate comparisons. We also review the main applications of the surveyed methods in personalised marketing, personalised medicine, and sociology. Finally, we summarise and discuss the available software packages and source codes in terms of their coverage of different methods and applicability to different datasets, and we provide general guidelines for method selection.

The Current Understanding of Precision Medicine and Personalised Medicine in Selected Research Disciplines: Study Protocol of a Systematic Concept Analysis

Introduction. The terms "precision medicine" and "personalised medicine" have become key terms in health-related research, and in science-related public communication. However, the application of these two concepts and their interpretation in various disciplines are heterogeneous, which also affects research translation and public awareness. This leads to confusion regarding the use and distinction of the two concepts. Methods and analysis. Our study aims at using Rodger's concept analysis method to systematically examine and distinguish the current understanding of the concepts "precision medicine" and "personalised medicine" in clinical medicine, biomedicine (incorporating genomics and bioinformatics), health services research; physics, chemistry, engineering; machine learning, and artificial intelligence, and to identify their respective attributes (clusters of characteristics) and surrogate and related terms. We will analyse similarities and differences in definitions in the respective disciplines and across different (sub)disciplines. The analysis procedure will include (1) a concept identification, (2) a setting, sample, and data source selection, (3) data collection, (4) data analysis and data summary, (5) identification of examples, and (6) identification of implications for further concept development. Ethics and dissemination. Following ethical and research standards, we will comprehensively report the methodology for a systematic analysis following Roger's[1] concept analysis method. Our systematic concept analysis will contribute to the clarification of the two concepts and distinction in their application in given settings and circumstances. Such a broader concept analysis will contribute to non-systematic syntheses of the concepts, or occasional systematic reviews on one of the concepts that have been published in specific disciplines, in order to facilitate interdisciplinary communication, translational medical research, and implementation science.

Atypical antipsychotic Lumateperone Beyond Schizophrenia: Seeking clarity in a time of Uncertainty

Lumateperone (ITI-007) is a serotonin 5HT2A tosylate salt with high affinity for dopamine D2 and D1 receptors and the serotonin transporter. It is unusual in that it controls serotonin, dopamine, and glutamate neurotransmission concurrently, all of which have been implicated in severe mental illness. Consider it a multi-targeted ligand and multifunctional modulator of the serotoninergic system with possible precognitive, antipsychotic, antidepressant, and anxiolytic properties. While lumateperone has been explored as a new agent for schizophrenia therapy, it also provides a unique therapeutic option for a range of other psychiatric and neurological diseases, including behavioural signs of dementia or Alzheimer's disease, sleep problems, and bipolar depression. Additionally, it had a better safety profile than placebo, with no significant extrapyramidal side effects, hyperprolactinemia, or changes in cardiometabolic or endocrine characteristics. Additional study is needed to validate and analyse lumateperone's effectiveness, as well as to identify prospective therapeutic targets. This article gives a comprehensive overview of the most notable results and potential future applications of this chemical in personalised medicine, particularly for neurodegenerative diseases.

Identifying the Steps Required to Effectively Implement Next-Generation Sequencing in Oncology at a National Level in Europe

Next-generation sequencing (NGS) may enable more focused and highly personalized cancer treatment, with the National Comprehensive Cancer Network and European Society for Medical Oncology guidelines now recommending NGS for daily clinical practice for several tumor types. However, NGS implementation, and therefore patient access, varies across Europe; a multi-stakeholder collaboration is needed to establish the conditions required to improve this discrepancy. In that regard, we set up European Alliance for Personalised Medicine (EAPM)-led expert panels during the first half of 2021, including key stakeholders from across 10 European countries covering medical, economic, patient, industry, and governmental expertise. We describe the outcomes of these panels in order to define and explore the necessary conditions for NGS implementation into routine clinical care to enable patient access, identify specific challenges in achieving them, and make short- and long-term recommendations. The main challenges identified relate to the demand for NGS tests (governance, clinical standardization, and awareness and education) and supply of tests (equitable reimbursement, infrastructure for conducting and validating tests, and testing access driven by evidence generation). Recommendations made to resolve each of these challenges should aid multi-stakeholder collaboration between national and European initiatives, to complement, support, and mutually reinforce efforts to improve patient care.

Treatment of kidney clear cell carcinoma, lung adenocarcinoma and glioblastoma cell lines with hydrogels made of DNA nanostars

Overcoming the systemic administration of chemotherapy to reduce drug toxicity and the application of personalised medicine are two of the major challenges in the treatment of cancer. To this aim,...

Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large dataset comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling) but are equally applicable to free energy perturbation calculations for which we expect essentially very similar results. Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behaviour. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

Personalized medicine: the future of Modern Medicine

Medical care is no longer a one-size-fits-all endeavour. There is a problem with the traditional or present systems of medical care because they were developed and tested on large groups of people. Consequently, the prescriptions prescribed are not suitable for every person. A certain number of medicines work very well for some people and some do not. Modern medicine relies on scientific evidence, including clinical trials, which is termed evidence-Based Medicine. It is expected that in the future, treatment will be based on algorithms that will take the patient’s genetic, epigenetic, and lifestyle characteristics into account, resulting in personalized medication.The drugs that your doctor recommends for you will be determined by your genetics, lifestyle, and environment, along with your symptoms of illness. Modern medicine has enabled humans to live longer and healthier lives.Personalized medicine is the way of thinking about medicine in the modern era. We will examine how personalized medicine will change healthcare, how artificial intelligence and personalised medicine can be combined to improve healthcare, the role of personalized medicine in pharmaceuticals, its application, and its future trajectory.

Metabolic phenotyping of tear fluid as a prognostic tool for personalised medicine exemplified by T2DM patients

Background/AimsOne goal of predictive, preventive, and personalised medicine is to improve the prediction and diagnosis of diseases, as well as to monitor therapeutic efficacy and to tailor individualised treatments with as little side effects as possible. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance. Here we have thus investigated the metabolic composition of human tears in comparison to finger sweat and evaluated whether tear analyses may provide insight into ocular and systemic disease mechanisms.MethodsIn addition to finger sweat, tear fluid was sampled from 20 healthy volunteers using commercially available Schirmer strips. Tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography was performed with optimized methods each for metabolites and eicosanoids. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects.ResultsTear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients. These findings highlight the potential diagnostic and prognostic power of tear fluid analyses, in addition to the promising methodological support for pharmacokinetic studies and patient compliance control.ConclusionsTear fluid analysis may support the development of clinical applications in the context of predictive, preventive, and personalised medicine as it reveals rich molecular information in a non-invasive way.

Immuno-Endocrinology of COVID-19: The Key Role of Sex Hormones

Epidemiological evidence shows clear gender disparities in the Coronavirus 2019 Disease (COVID-19) severity and fatality. This may reflect the contribution of gender-related factors, such as sex hormones, to COVID-19 pathogenesis. However, the mechanism linking gender disparities to COVID-19 severity is still poorly understood. In this review, we will pinpoint several elements involved in COVID-19 pathogenesis that are regulated by the two main sex hormones, estrogen and androgen. These include tissue specific gene regulation of SARS-CoV2 entry factors, innate and adaptive immune responses to infection, immunometabolism, and susceptibility to tissue injury by cytopathic effect or hyper-inflammatory response. We will discuss the mechanistic link between sex hormone regulation of COVID-19 pathogenetic factors and disease severity. Finally, we will summarize current evidence from clinical studies and trials targeting sex hormones and their signalling in COVID-19. A better understanding of the role of sex hormones in COVID-19 may identify targets for therapeutic intervention and allow optimization of treatment outcomes towards gender-based personalised medicine.

Resistance mechanisms to inhibitors of p53-MDM2 interactions in cancer therapy: can we overcome them?

Since the discovery of the first MDM2 inhibitors, we have gained deeper insights into the cellular roles of MDM2 and p53. In this review, we focus on MDM2 inhibitors that bind to the p53-binding domain of MDM2 and aim to disrupt the binding of MDM2 to p53. We describe the basic mechanism of action of these MDM2 inhibitors, such as nutlin-3a, summarise the determinants of sensitivity to MDM2 inhibition from p53-dependent and p53-independent points of view and discuss the problems with innate and acquired resistance to MDM2 inhibition. Despite progress in MDM2 inhibitor design and ongoing clinical trials, their broad use in cancer treatment is not fulfilling expectations in heterogenous human cancers. We assess the MDM2 inhibitor types in clinical trials and provide an overview of possible sources of resistance to MDM2 inhibition, underlining the need for patient stratification based on these aspects to gain better clinical responses, including the use of combination therapies for personalised medicine.