2015 07-03 Nanonext NL Alain van Gool, AmsterdamAlain van Gool
The document discusses implementing personalized healthcare through measuring biomarkers. It notes that while many biomarkers have been discovered, few are validated and applied in diagnostic tests. There is also a gap in translating biomarkers into point-of-care applications. The document advocates for open innovation networks to help validate biomarkers across multiple centers and standardize clinical applications. Ultimately, the focus of personalized healthcare should be on the patient by providing individualized follow-up based on their molecular and clinical measurements.
2015 09-14 Precision Medicine 2015, London, Alain van GoolAlain van Gool
Outline of my view hoe personalized health(care) is more than just targeted medicines, also including personal motivation and actions towards disease prevention. It also outlines 4 key factors that should be in order for optimal personalized health(care): 1. start with patients first, 2. Accelerate translation research to application, 3. Copy best practice, 4. Spread the word.
Alain van Gool presented on biomarkers in personalized healthcare. He discussed how personalized medicine is shifting to personalized healthcare with a systems view that considers multiple factors. Exponential technologies will transform healthcare in the coming years through digital medicine, self-diagnosis, artificial intelligence, and big data. However, gaps remain in translating biomarker discoveries into clinical applications and demonstrating added value. Open innovation is needed to accelerate biomarker development through multi-center validation studies.
The reality of moving towards precision medicineElia Stupka
How do we move towards precision medicine? How can we deliver on the big data in health promise? Who will be the enablers and players? Pharma, Big Tech, or newcomers?
2019 06-19 Dutch association for clinical chemistry and laboratory medicine -...Alain van Gool
Sharing my views on how X-omics biomarker analyses through next gen sequencing and mass spectrometry will change the landscape of diagnostics and clinical chemistry in the near future.
This document provides information about Dr. Kirtan Vyas, including his educational background and qualifications. It lists that he has a M.S. in Obstetrics/Gynecology, was a gold medalist from Gujarat University, was first in the Gujarat Public Service Commission, has fellowships in gynec endoscopy and ultrasonography, has publications in international journals, has presented at conferences, is faculty at state and national conferences, and currently works as an assistant professor at P.D.U. Medical College and Hospital in Rajkot.
2015 07-03 Nanonext NL Alain van Gool, AmsterdamAlain van Gool
The document discusses implementing personalized healthcare through measuring biomarkers. It notes that while many biomarkers have been discovered, few are validated and applied in diagnostic tests. There is also a gap in translating biomarkers into point-of-care applications. The document advocates for open innovation networks to help validate biomarkers across multiple centers and standardize clinical applications. Ultimately, the focus of personalized healthcare should be on the patient by providing individualized follow-up based on their molecular and clinical measurements.
2015 09-14 Precision Medicine 2015, London, Alain van GoolAlain van Gool
Outline of my view hoe personalized health(care) is more than just targeted medicines, also including personal motivation and actions towards disease prevention. It also outlines 4 key factors that should be in order for optimal personalized health(care): 1. start with patients first, 2. Accelerate translation research to application, 3. Copy best practice, 4. Spread the word.
Alain van Gool presented on biomarkers in personalized healthcare. He discussed how personalized medicine is shifting to personalized healthcare with a systems view that considers multiple factors. Exponential technologies will transform healthcare in the coming years through digital medicine, self-diagnosis, artificial intelligence, and big data. However, gaps remain in translating biomarker discoveries into clinical applications and demonstrating added value. Open innovation is needed to accelerate biomarker development through multi-center validation studies.
The reality of moving towards precision medicineElia Stupka
How do we move towards precision medicine? How can we deliver on the big data in health promise? Who will be the enablers and players? Pharma, Big Tech, or newcomers?
2019 06-19 Dutch association for clinical chemistry and laboratory medicine -...Alain van Gool
Sharing my views on how X-omics biomarker analyses through next gen sequencing and mass spectrometry will change the landscape of diagnostics and clinical chemistry in the near future.
This document provides information about Dr. Kirtan Vyas, including his educational background and qualifications. It lists that he has a M.S. in Obstetrics/Gynecology, was a gold medalist from Gujarat University, was first in the Gujarat Public Service Commission, has fellowships in gynec endoscopy and ultrasonography, has publications in international journals, has presented at conferences, is faculty at state and national conferences, and currently works as an assistant professor at P.D.U. Medical College and Hospital in Rajkot.
First Pediatric Concussion Treatment Guidelines by CDC
mild traumatic brain injury (mTBI)
recommendations on the diagnosis, prognosis, and management/treatment of pediatric mTBI
review of pediatric mTBI scientific evidence
Refrain from routinely imaging children to diagnose mTBI
This document provides an executive summary of the updated guidelines for managing pediatric severe traumatic brain injury (TBI). The guidelines were updated based on new research identified since the second edition. The update includes 22 total recommendations, with nine being new or revised. New recommendations address neuroimaging, hyperosmolar therapy, analgesics/sedatives, seizure prophylaxis, temperature control/hypothermia, and nutrition. None are level I evidence, three are level II, and 19 are level III. An accompanying algorithm supplements the recommendations with expert consensus where evidence is lacking. The full guidelines and appendices are available electronically and contain detailed information on the studies and methodology. The intention is to continue updating the guidelines as new evidence emerges.
The document discusses the importance of causal frameworks and artificial intelligence (AI) for health research. It provides examples of how causal diagrams (DAGs) have been useful in health research by correcting an analytic mistake and evaluating survival bias. The document also presents a simulation study examining potential collider bias in racial disparities in stroke risk between middle and late life. The simulation compares different causal structures and finds bias only in structures where an unmeasured factor influences both mortality and stroke risk.
The document discusses opportunities for improving healthcare through precision medicine and integrating genomic and quantified self data. It identifies several pain points in the current healthcare system such as inefficient appointments and a lack of preventative care. Interviews with patients and providers revealed that neither group fully understands genetic data and they desire more participation. The aim is to present a vision for how genomic data could influence health services through opportunities like providing actionable steps based on genetic counseling, combining family history with genomic data, and enabling preventative health measures from a young age.
This document summarizes a panel discussion on transforming patient-generated health data for wellness and biomedical research. The panelists were Susan Peterson, Katherine Kim, Fernando Martin-Sanchez, Cagatay Demiralp, and Pei-Yun Sabrina Hsueh (moderator). Peterson discussed using sensors and mobile apps to monitor cancer patients undergoing radiation therapy to detect early signs of dehydration. Kim discussed leveraging patient data for personalized care coordination. Martin-Sanchez discussed generating evidence from patient data to inform research. Demiralp discussed visualization of patient data. Overall the panel explored opportunities and barriers to using patient-generated data from behavioral sensing to clinical decision support.
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"CTSI at UCSF
Keith R. Yamamoto, PhD — Opening Remarks – Precision Medicine
Vice Chancellor for Research
Executive Vice Dean of the School of Medicine
Professor of Cellular and Molecular Pharmacology
UCSF
This document summarizes a presentation on new sources of big data for precision medicine. It discusses how new data sources like genomics, the human microbiome, epigenomics, and the exposome are generating large amounts of data. It then covers the evolution of precision medicine from concepts like personalized medicine and how strategic initiatives in the UK and US are supporting precision medicine research through funding programs and projects like the Cancer Genome Atlas, eMERGE, and exposome studies. The presentation raises the question of whether we are ready for precision medicine given these new data sources and research efforts.
Systems Medicine: an introduction to the application of systems biology to health care applications. A prime for engineers, physicist, and mathematicians interested in a career in biomedicine
From Bits to Bedside: Translating Big Data into Precision Medicine and Digita...Dexter Hadley
Lecture Objectives:
1) To use examples from my research to define and introduce the ideals of precision medicine and digital health. 2) To introduce how large scale population-wide analysis of data can be used to facilitate these two ideals. 3) To introduce how freely available open data can be used to facilitate these two ideals. 4) To show how mobile technology can be used to facilitate these two ideals.
Precision Medicine is now a funded NIH initiative and an organic movement in the clinic and at the research institute. Based on work with Genomics England, multiple large pharmaceutical firms, and research hospitals, attendees will learn about the best practices for epidemiology, signal detection, research, and the clinical diagnostics associated with Precision Medicine, including the development of high-scale bio-repositories that link traditional patient data with genomic information. Come hear about how leadership, collaboration, consent, and compute can lead to success or failure in your Precision Medicine initiative, and how to bring your stakeholders together for an aligned mission response.
The document discusses using wearables and sensors in clinical trials. It notes opportunities like more realistic outcomes measures through continuous passive data collection. However, there are also challenges like concerns about device accuracy and privacy. Ensuring data standards and addressing issues around algorithms, privacy and FDA approval will be important for leveraging consumer devices in clinical trials.
Evidence based medicine scenario ExampleHatem Hussain
Evidence based medicine scenario Example for Acute appendicitis diagnosis, show how to formulate answerable clinical question using PICO.
Note: this presentation is only for learning and general knowledge and you should not use any information mentioned in with out physician consultation.
This document discusses how analyzing the large amounts of biomedical data now available can help discover new drugs and diagnostics. It notes there are now over 300 trillion points of biomedical data from sources like gene expression studies and electronic health records. The author describes how their research group has used various public big data sources to identify potential new markers for preeclampsia and find that an anti-seizure drug shows activity against inflammatory bowel disease and an anti-depressant against small cell lung cancer in animal models. They discuss the process of moving such findings from initial data analysis to validation and company formation to develop them into new therapies or diagnostics.
The document discusses limitations of several medical studies and the importance of critically evaluating press releases and media coverage of new research. It provides examples of limitations that should be acknowledged, such as small sample sizes, lack of blinding, potential for bias, and lack of generalizability. The document advocates getting the full text of studies, asking authors questions to understand limitations and implications, considering alternative explanations, and finding perspectives from outside experts rather than just study authors. Reporters are advised to look at relevance, costs, existing alternatives, and other angles beyond initial claims in order to provide accurate context and avoid overstating findings.
Color correction of morbid conditions using Strannik Technology on gastroente...tzefira44
The document discusses the use of the medical software system "Strannik" to diagnose and treat gastrointestinal diseases through non-invasive virtual scanning. It analyzed data from 847 patients examined using "Strannik" and found the system could diagnose diseases with 93% accuracy, sometimes detecting conditions earlier than traditional methods. Treatment using "Strannik's" color correction and signals therapy was also compared to traditional drug-based therapy, finding color correction took slightly longer but improved overall health and avoided side effects of medications.
The values of clinical practice - Jordi VarelaJordi Varela
Three key principles will guide clinical practice: adding value to patient health, organizing doctors according to clinical processes, and measuring outcomes adjusted for risk and cost. Right care considers benefits and harms, is patient-centered, and evidence-based. Half of surgeries and clinical trials lack evidence to support them. Overdiagnosis leads to unnecessary treatment complications. Fragmented care for chronic patients results in clinical instability, unnecessary tests and costs. Clinical value practices aim to reduce wasteful spending through protocols, teamwork and learning from errors.
This document lists publications from Nathan Hutting and others on developing and evaluating a self-management program called "Control CANS" for employees suffering from arm, neck, or shoulder complaints. It describes randomized controlled trials and process evaluations that found the program helped participants cope at work. Additionally, it lists publications by Sarah Detaille and others on developing self-management programs for employees with chronic diseases using an intervention mapping approach.
BM THESIS HTA LIT BM THESIS De Kinderen et al (2013)Roel Rinkens
The document discusses the economic burden of side effects from antiepileptic drugs (AEDs). It estimates the annual healthcare costs, patient and family costs, and other costs associated with common side effects experienced by 203 epilepsy patients in the Netherlands. The total estimated societal cost per patient per year is €20,751 (US$26,675), including healthcare costs (€4,458), patient and family costs like informal care (€10,526), and other costs like lost productivity (€5,761). When examined separately, the most to least expensive side effect categories were: other (€13,228), behavioral (€9,689), general health (€7,454), cognitive (€7,
This document discusses cardiovascular risk and adherence to treatment. It defines key terms like adherence, compliance, persistence, and non-adherence. It notes that poor adherence is a major reason for suboptimal clinical benefits. It also discusses factors that influence adherence like the medication, patient, and healthcare system. Non-adherence can increase risks of stroke, death, hospitalizations and costs. Long-term adherence to medications for conditions like hypertension and statins is often low, around 50%. Improving adherence requires addressing multiple barriers and ensuring patients are involved in treatment decisions.
The document discusses how genes expressed in the brain influence its development and functions. It notes that at least a third of human genes are expressed in the brain, the highest proportion of any organ. These genes determine brain architecture and functions like movement, thinking, and behavior. The document also summarizes several specific genes linked to various brain-related conditions and disorders like schizophrenia.
This document discusses neuroinformatics, which combines neuroscience and information science. It provides an agenda for the topics to be covered, including an introduction to neuroinformatics, database development and management, an overview of neuroimaging techniques, computational neuroscience modeling, current research applications, and challenges. Single neuron modeling approaches like Hodgkin-Huxley and cable theory are explained. Current areas of research discussed are brain-gene ontology, human brain mapping atlases, and brain-computer interfaces.
First Pediatric Concussion Treatment Guidelines by CDC
mild traumatic brain injury (mTBI)
recommendations on the diagnosis, prognosis, and management/treatment of pediatric mTBI
review of pediatric mTBI scientific evidence
Refrain from routinely imaging children to diagnose mTBI
This document provides an executive summary of the updated guidelines for managing pediatric severe traumatic brain injury (TBI). The guidelines were updated based on new research identified since the second edition. The update includes 22 total recommendations, with nine being new or revised. New recommendations address neuroimaging, hyperosmolar therapy, analgesics/sedatives, seizure prophylaxis, temperature control/hypothermia, and nutrition. None are level I evidence, three are level II, and 19 are level III. An accompanying algorithm supplements the recommendations with expert consensus where evidence is lacking. The full guidelines and appendices are available electronically and contain detailed information on the studies and methodology. The intention is to continue updating the guidelines as new evidence emerges.
The document discusses the importance of causal frameworks and artificial intelligence (AI) for health research. It provides examples of how causal diagrams (DAGs) have been useful in health research by correcting an analytic mistake and evaluating survival bias. The document also presents a simulation study examining potential collider bias in racial disparities in stroke risk between middle and late life. The simulation compares different causal structures and finds bias only in structures where an unmeasured factor influences both mortality and stroke risk.
The document discusses opportunities for improving healthcare through precision medicine and integrating genomic and quantified self data. It identifies several pain points in the current healthcare system such as inefficient appointments and a lack of preventative care. Interviews with patients and providers revealed that neither group fully understands genetic data and they desire more participation. The aim is to present a vision for how genomic data could influence health services through opportunities like providing actionable steps based on genetic counseling, combining family history with genomic data, and enabling preventative health measures from a young age.
This document summarizes a panel discussion on transforming patient-generated health data for wellness and biomedical research. The panelists were Susan Peterson, Katherine Kim, Fernando Martin-Sanchez, Cagatay Demiralp, and Pei-Yun Sabrina Hsueh (moderator). Peterson discussed using sensors and mobile apps to monitor cancer patients undergoing radiation therapy to detect early signs of dehydration. Kim discussed leveraging patient data for personalized care coordination. Martin-Sanchez discussed generating evidence from patient data to inform research. Demiralp discussed visualization of patient data. Overall the panel explored opportunities and barriers to using patient-generated data from behavioral sensing to clinical decision support.
UCSF Informatics Day 2014 - Keith R. Yamamoto, "Precision Medicine"CTSI at UCSF
Keith R. Yamamoto, PhD — Opening Remarks – Precision Medicine
Vice Chancellor for Research
Executive Vice Dean of the School of Medicine
Professor of Cellular and Molecular Pharmacology
UCSF
This document summarizes a presentation on new sources of big data for precision medicine. It discusses how new data sources like genomics, the human microbiome, epigenomics, and the exposome are generating large amounts of data. It then covers the evolution of precision medicine from concepts like personalized medicine and how strategic initiatives in the UK and US are supporting precision medicine research through funding programs and projects like the Cancer Genome Atlas, eMERGE, and exposome studies. The presentation raises the question of whether we are ready for precision medicine given these new data sources and research efforts.
Systems Medicine: an introduction to the application of systems biology to health care applications. A prime for engineers, physicist, and mathematicians interested in a career in biomedicine
From Bits to Bedside: Translating Big Data into Precision Medicine and Digita...Dexter Hadley
Lecture Objectives:
1) To use examples from my research to define and introduce the ideals of precision medicine and digital health. 2) To introduce how large scale population-wide analysis of data can be used to facilitate these two ideals. 3) To introduce how freely available open data can be used to facilitate these two ideals. 4) To show how mobile technology can be used to facilitate these two ideals.
Precision Medicine is now a funded NIH initiative and an organic movement in the clinic and at the research institute. Based on work with Genomics England, multiple large pharmaceutical firms, and research hospitals, attendees will learn about the best practices for epidemiology, signal detection, research, and the clinical diagnostics associated with Precision Medicine, including the development of high-scale bio-repositories that link traditional patient data with genomic information. Come hear about how leadership, collaboration, consent, and compute can lead to success or failure in your Precision Medicine initiative, and how to bring your stakeholders together for an aligned mission response.
The document discusses using wearables and sensors in clinical trials. It notes opportunities like more realistic outcomes measures through continuous passive data collection. However, there are also challenges like concerns about device accuracy and privacy. Ensuring data standards and addressing issues around algorithms, privacy and FDA approval will be important for leveraging consumer devices in clinical trials.
Evidence based medicine scenario ExampleHatem Hussain
Evidence based medicine scenario Example for Acute appendicitis diagnosis, show how to formulate answerable clinical question using PICO.
Note: this presentation is only for learning and general knowledge and you should not use any information mentioned in with out physician consultation.
This document discusses how analyzing the large amounts of biomedical data now available can help discover new drugs and diagnostics. It notes there are now over 300 trillion points of biomedical data from sources like gene expression studies and electronic health records. The author describes how their research group has used various public big data sources to identify potential new markers for preeclampsia and find that an anti-seizure drug shows activity against inflammatory bowel disease and an anti-depressant against small cell lung cancer in animal models. They discuss the process of moving such findings from initial data analysis to validation and company formation to develop them into new therapies or diagnostics.
The document discusses limitations of several medical studies and the importance of critically evaluating press releases and media coverage of new research. It provides examples of limitations that should be acknowledged, such as small sample sizes, lack of blinding, potential for bias, and lack of generalizability. The document advocates getting the full text of studies, asking authors questions to understand limitations and implications, considering alternative explanations, and finding perspectives from outside experts rather than just study authors. Reporters are advised to look at relevance, costs, existing alternatives, and other angles beyond initial claims in order to provide accurate context and avoid overstating findings.
Color correction of morbid conditions using Strannik Technology on gastroente...tzefira44
The document discusses the use of the medical software system "Strannik" to diagnose and treat gastrointestinal diseases through non-invasive virtual scanning. It analyzed data from 847 patients examined using "Strannik" and found the system could diagnose diseases with 93% accuracy, sometimes detecting conditions earlier than traditional methods. Treatment using "Strannik's" color correction and signals therapy was also compared to traditional drug-based therapy, finding color correction took slightly longer but improved overall health and avoided side effects of medications.
The values of clinical practice - Jordi VarelaJordi Varela
Three key principles will guide clinical practice: adding value to patient health, organizing doctors according to clinical processes, and measuring outcomes adjusted for risk and cost. Right care considers benefits and harms, is patient-centered, and evidence-based. Half of surgeries and clinical trials lack evidence to support them. Overdiagnosis leads to unnecessary treatment complications. Fragmented care for chronic patients results in clinical instability, unnecessary tests and costs. Clinical value practices aim to reduce wasteful spending through protocols, teamwork and learning from errors.
This document lists publications from Nathan Hutting and others on developing and evaluating a self-management program called "Control CANS" for employees suffering from arm, neck, or shoulder complaints. It describes randomized controlled trials and process evaluations that found the program helped participants cope at work. Additionally, it lists publications by Sarah Detaille and others on developing self-management programs for employees with chronic diseases using an intervention mapping approach.
BM THESIS HTA LIT BM THESIS De Kinderen et al (2013)Roel Rinkens
The document discusses the economic burden of side effects from antiepileptic drugs (AEDs). It estimates the annual healthcare costs, patient and family costs, and other costs associated with common side effects experienced by 203 epilepsy patients in the Netherlands. The total estimated societal cost per patient per year is €20,751 (US$26,675), including healthcare costs (€4,458), patient and family costs like informal care (€10,526), and other costs like lost productivity (€5,761). When examined separately, the most to least expensive side effect categories were: other (€13,228), behavioral (€9,689), general health (€7,454), cognitive (€7,
This document discusses cardiovascular risk and adherence to treatment. It defines key terms like adherence, compliance, persistence, and non-adherence. It notes that poor adherence is a major reason for suboptimal clinical benefits. It also discusses factors that influence adherence like the medication, patient, and healthcare system. Non-adherence can increase risks of stroke, death, hospitalizations and costs. Long-term adherence to medications for conditions like hypertension and statins is often low, around 50%. Improving adherence requires addressing multiple barriers and ensuring patients are involved in treatment decisions.
The document discusses how genes expressed in the brain influence its development and functions. It notes that at least a third of human genes are expressed in the brain, the highest proportion of any organ. These genes determine brain architecture and functions like movement, thinking, and behavior. The document also summarizes several specific genes linked to various brain-related conditions and disorders like schizophrenia.
This document discusses neuroinformatics, which combines neuroscience and information science. It provides an agenda for the topics to be covered, including an introduction to neuroinformatics, database development and management, an overview of neuroimaging techniques, computational neuroscience modeling, current research applications, and challenges. Single neuron modeling approaches like Hodgkin-Huxley and cable theory are explained. Current areas of research discussed are brain-gene ontology, human brain mapping atlases, and brain-computer interfaces.
Personalized Health and Care: IT-enabled Personalized HealthcareIBM HealthCare
This document discusses how personalized healthcare (PHC) could help address issues with the science of health promotion and care delivery. PHC aims to use broader patient data and more complete clinical knowledge to promote health, predict/prevent diseases, aid early detection/diagnosis, and manage diseases. However, PHC requires a powerful health information technology environment capable of capturing, storing, analyzing and sharing extensive patient data and clinical knowledge. The current HIT environment is insufficient for PHC and must become more open, robust and able to incorporate continually generated clinical knowledge into decision making.
PwC is a global professional services firm that provides audit, tax, and consulting services. It has established a Personalized Medicine practice to help clients respond to trends in personalized healthcare. PwC has worked on several initiatives involving personalized medicine, including establishing a genome research institute in Arizona and facilitating partnerships between institutions in the US and Luxembourg to advance bioscience research. PwC utilizes surveys, interviews, and research to develop reports on trends in healthcare, including the growth of personalized medicine.
Personalized Health Care: The Foundation of Rational Health ReformRyan Squire
1) Personalized health care is the foundation of rational health reform and involves understanding an individual's health risks, disease progression, and response to treatment through tools like genomics, proteomics, and predictive models.
2) This paradigm shift moves away from reactive, disease-oriented care to predictive, preventative, and personalized approaches through a patient's personalized health plan.
3) Key factors in successful health reform include universal access to health education and planning, delivery system integration, and payment reform to support personalized and preventative approaches.
The document discusses the need for personalized health care as the key to meaningful health care reform. It outlines how medicine has progressed from focusing on single factors to understanding disease as complex with multiple interacting factors. Personalized health care involves using tools like genomics, biomarkers and clinical risk models to quantify individual health risks, monitor disease progression, select targeted therapies, and create personalized health plans and treatment timelines. The document provides an example of how this approach could be used to create a personalized cancer care plan.
The document discusses several key healthcare trends and opportunities:
1) Demographic shifts like population aging are increasing demand for healthcare services. Chronic diseases are also rising due to lifestyle changes.
2) Technological advances and the empowered consumer are transforming healthcare delivery through telemedicine, mobile health apps, and more consumer-centric models.
3) New entrants like technology companies are disrupting the industry by introducing new products and services, while incumbents must decide whether to partner or compete with these new players.
1) The document describes steps in a bioinformatics analysis pipeline that uses BLAST and CLUSTALW to perform sequence alignment and clustering on a query protein sequence from Homo sapiens (hsa:6469).
2) Each step is contained in a separate Ruby script (step10.rb through step60.rb) that retrieves data through REST/SOAP calls and passes output through text files.
3) The final step performs a multiple sequence alignment of BLAST hits passing the E-value threshold using CLUSTALW through a SOAP call and outputs the result.
The document discusses how epigenetics, through mechanisms like DNA methylation and histone modification, can influence gene expression and traits without changing the underlying DNA sequence. It provides examples of how environmental factors and early life experiences can alter the epigenome in ways that affect health conditions later in life, including cancer, mental illnesses like schizophrenia, and neurodevelopmental disorders. Epigenetic therapies targeting these epigenetic changes offer promising new medical approaches.
Clustal X help to the Bioinformatics candidate to predicts the Multiple Sequence Alignment and Phylogenetic Analysis for given a nuber of Gene Sequences of varrious organism,and find the evolutionary relationship.
The Extreme Future of Health Care 2014James Canton
Radical trends in health care and medicine will change business and society. This presentation fresh from Dr. James Canton's New Keynote Presentation and from his upcoming new book looks at the trends in biotech, synthetic biology, digital health, genomics, wellness and regenerative medicine that will shape the near future of our world and health. Find out what's next and how to prepare today. For more info see http://globalfuturist.com
Regenerative medicine uses stem cell therapy and tissue engineering to replace damaged cells and repair organs. It aims to treat age-related diseases by generating replacement cells from stem cells. Regenerative medicine works by isolating cells, manipulating and expanding them, and transplanting the modified cells back into patients to replace malfunctioning cells. Pioneers in the field have used this approach to successfully engineer tissues like bladders and windpipes. Induced pluripotent stem cells allow adult cells to be reprogrammed and have potential for personalized regenerative medicine without ethical concerns of embryonic stem cells. Regenerative medicine holds promise for treating many currently incurable diseases.
A look at the key trends and challenges in applying Big Data to transform healthcare by supporting research, self care, providers and building ecosystems. Purchase the report here: https://gumroad.com/l/PlXP
This document discusses emerging trends in the future of health care, including increased personalization and prevention, faster innovations, and new technologies like nanomedicine, regenerative medicine, and medical androids. Population growth and aging, as well as a shift toward consumer-driven health and lifestyle management, will be major drivers of change. New diagnostic tools and personalized treatments enabled by genomics, proteomics, and other converging technologies may help enhance human performance and longevity.
Understanding Risk Stratification, Comorbidities, and the Future of HealthcareHealth Catalyst
Risk stratification is essential to effective population health management. To know which patients require what level of care, a platform for separating patients into high-risk, low-risk, and rising-risk is necessary. Several methods for stratifying a population by risk include: Hierarchical Condition Categories (HCCs), Adjusted Clinical Groups (ACG), Elder Risk Assessment (ERA), Chronic Comorbidity Count (CCC), Minnesota Tiering, and Charlson Comorbidity Measure. At Health Catalyst, we use an analytics application called the Risk Model Analyzer to stratify patients into risk categories. This becomes a powerful tool for filtering populations to find higher-risk patients.
The Future of Personalized Health Care: Predictive Analytics by @Rock_HealthRock Health
View the archived webinar here: https://www.youtube.com/watch?v=UJak41hIDWc
How can we use new and existing sources of data to deliver better, personalized care? Predictive analytics underlies what has always been conducted by doctors through their training, experience, and decision-making. Dozens of new digital products have hit the market and $1.9B has flowed into the space since 2011—but what does it take for an algorithm to accurately and reliably impact care?
Purchase the report here: https://gumroad.com/l/gzbzV
Three Approaches to Predictive Analytics in HealthcareHealth Catalyst
Predictive analytics in healthcare must be timely, role-specific, and actionable to be successful. There are also three common types of healthcare predictive analytics: Risk scores (risk stratification using CMS-HCC or other models), What-if scenarios (simulations of specific outcomes given a certain combination of events, and Geo-spatial analytics (mapping a geographical location’s patient disease burden). The common thread in all of these is the element of action, or specifically, the intervention that really matters in healthcare predictive analytics.
The social media landscape is evolving quickly too; Facebook still dominates - and continues to grow - but the remaining spots in the top 5 of our latest platform rankings are held by mobile messenger services.....
This document discusses the Radboud University Medical Center (Radboudumc) in Nijmegen, Netherlands. It provides details about:
1. Radboudumc's mission to have a significant impact on healthcare through personalized healthcare and the patient as partner approach.
2. The core activities of patient care, research, and education conducted by 11,000 colleagues across 52 departments and serving 3,300 students.
3. The 18 Technology Centers at Radboudumc that provide technological expertise and resources to approximately 1,600 internal and external users across 140 consortia working in areas like genomics, imaging, and clinical trials.
Un documento describe una estrategia centrada en el cliente para el comercio electrónico que incluye considerar al cliente en todas las áreas como plataforma, infraestructura, producto, logística, marketing, cobranza y métricas clave para implementar, medir y analizar el rendimiento de la estrategia.
2015 12-09 Opening Radboud Translational Medicine, Nijmegen, Alain van GoolAlain van Gool
Keynote opening lecture at the grand opening of our new cyclotron facility, embedded in Radboud Translational Medicine and part of our Radboudumc Technology Centers. See http://www.radboudtranslationalmedicine.nl/nl/ for details.
2015 06-02 Steering group 'Personalized Medicine: eligible or not'Alain van Gool
Update for the steering group of the project "Personalized Medcine: eligble or not?", aiming to define whether and how to implement pharmacogenetic screening by first line care practitioners.
2016 05-24 Kick-off The Danish Biomarker Network, Copenhagen, Alain van GoolAlain van Gool
Keynote lecture given at the kick-off of The Danish Biomarker Network in Copenhagen for a great audience of enthousiastic patients, biotech/pharma developers and ICT experts.
2015 05-20 Radboudumc REshape breakfast meeting Alain van GoolAlain van Gool
This document discusses biomarkers in personalized healthcare and moving beyond targeted medicine. It provides an overview of the speaker's background and experience in academia, pharmaceutical industry, and medical school related to biomarkers, omics technologies, and personalized healthcare. It then discusses the exponential developments in biomarker technologies, the need for a systems biology view in personalized healthcare, and translation challenges in bridging the gap between biomarkers and personalized interventions for patients.
2016 08-22 Radboud Grand Round, Nijmegen, Alain van GoolAlain van Gool
Interactive lecture with a large group of healthcare professionals, scientists and patients to illustrate developments in personalized healthcare and the role of technology to support science, innovations and medical impact. (slides in English)
2015 01-06 Oudejaarssymposium Personalized Healthcare, GroningenAlain van Gool
Personalized healthcare is moving beyond just targeted medicine to become more patient-centered. Biomarkers are playing an evolving role, from diagnosis to translational medicine to personalized healthcare. Radboud University Medical Center aims to have a significant impact on healthcare through their focus on personalized healthcare and including the patient as a partner. Their integrated translational research and diagnostic laboratory develops biomarkers through various omics technologies for personalized diagnosis and treatment.
2020 08-28 SensUs Event 2020 keynote, Eindhoven, Alain van GoolAlain van Gool
Closing keynote for international students participating in the SensUs Event 2020, where they designed and created a novel sensor for drug level monitoring in epilepsy treatment. Lecture outlined innovations in biomarkers in personalized health(care).
2013-10-02 Dutch CC symposium on Personalized Healthcare, EdeAlain van Gool
This document summarizes a presentation about companion diagnostics and personalized healthcare. It discusses how companion diagnostics can identify the right drug, dose, and timing for a patient by using biomarkers to characterize biological systems and diseases. It provides examples of companion diagnostic use in oncology and challenges in biomarker development and validation. Overall it advocates applying well-characterized therapies guided by biomarkers to better understand and treat disease in a personalized manner.
2013-04-23 Top Institute Pharma Spring meeting, UtrechtAlain van Gool
Companion diagnostics use biomarkers as diagnostic tools to identify patients who will respond well to specific drug therapies. The presentation discusses the increasing use of companion diagnostics in oncology drug development and clinical trials. It provides examples of biomarkers used to identify patients with melanoma who will benefit from BRAF inhibitor drugs. While some biomarkers like BRAFV600E mutations are useful targets, tumor heterogeneity poses a challenge for companion diagnostics. The presentation calls for improving the pipeline for validating biomarkers and developing them into clinical diagnostic tests.
2016-02-18 Innovation for Health 2016 conference, Rotterdam Alain van GoolAlain van Gool
Lecture on personalized healthcare in a great session at the Innovation for Health 2016 conference, discussing opportunities and challenges with 800 scientists, enterpreneurs and care professionals.
2018 11-02 Healthy Brain Cohort progress meeting, Nijmegen, Alain van GoolAlain van Gool
Highlights and anecdotes from my experiences in interdisciplinary research in big data for personalized healthcare whilst working in Europe, USA and Singapore
This document discusses bridging system biology research to personalized healthcare. It summarizes:
1) System biology considers genetics, metabolism, mental state, and environment to yield personalized profiles for personalized healthcare solutions using lifestyle, food, and/or pharmaceutical interventions.
2) Personalized healthcare involves stratifying patients using multilevel diagnosis, respecting patient treatment preferences, and involving care communities.
3) Applying novel technologies in clinical care requires a balance of research/technology push to add useful biomarkers with considerations of daily practice needs and costs.
2014 09-25 MipTec Europe's Drug Discovery eventAlain van Gool
This document discusses biomarkers in personalized healthcare and medicine. It is presented by Professor Alain van Gool, who has experience in both academia and the pharmaceutical industry researching biomarkers and personalized health. The presentation discusses the evolving role of biomarkers from diagnosis to personalized healthcare and medicine. It emphasizes the need for a systems approach using multi-omics data to develop personalized diagnostics and combination therapies for complex diseases like diabetes. Personalized healthcare is about tailoring treatment to each individual based on their molecular profiling and preferences.
2018 11-26 KNAW-AcTI symposium Personalized Health, Amsterdam, Alain van GoolAlain van Gool
Lecture at a citizen discussion evening, reviewing the promises and (ethical) considerations of technology developments to support personalized health, organised by the Royal Academy of Sciences and the Netherlands Academy of Technology and Innovation.
2016 03-17 Health Valley Event 2016, Alain van GoolAlain van Gool
Sharing thoughts during the session Personalized Medicine at the Health Valley Event 2016, which again was a great event with 1100+ health care innovators !
2014 02-24 Oxford Global biomarker congress, ManchesterAlain van Gool
This document summarizes a presentation given by Alain van Gool on biomarkers in a changing world. It discusses the shift from personalized medicine to personalized healthcare, which takes a more holistic systems view of an individual. It also notes disruptive technologies that can accelerate biomarker development and the need to translate biomarkers into useful tools. Throughout, it provides examples of challenges like tumor heterogeneity and factors beyond genetics that influence disease and response to treatment.
2023-11-14 Biomarkers Europe 2023, Berlin, Alain van Gool.pdfAlain van Gool
Lecture at the Biomarkers Europe 2023 conference for an audience of pharma scientists and omics/data solution providers. I outlined several initiatives of potential interest and discussed development of our sensitive personalized clinical biomarker test for minimal residual disease monitoring in multiple myeloma.
2023-11-09 HealthRI Biobanking day_Amsterdam_Alain van Gool.pdfAlain van Gool
Examples of lessons learned in Omics-based biomarker studies from myself and colleagues in X-omics and EATRIS, for an audience of biobankers, researchers and diagnostic/clinical chemistry experts.
2023-04-20 EATRIS-Plus Summerschool, Lisbon, Alain van GoolAlain van Gool
Closing keynote lecture at the EATRIS-Plus summerschool on personalised medicine, outlining developments, opportunities, challenges and recommendations to do next in this exciting era of personalised medicine.
2022-11-23 DTL Future of data-driven life sciences, Utrecht, Alain van Gool.pdfAlain van Gool
A pitch on directions to improve experimental reproducibility, illustrated by examples of past experiences. I made the plee to move from 'Proudly invented here' to 'Proudly copyied from', to re-use each other's eperiences in successes and failures.
2022-10-12 The future of population health_Alain van Gool.pdfAlain van Gool
1) Exponential developments in omics technologies like genomics, proteomics, and metabolomics are driving more personalized approaches to healthcare.
2) Mass spectrometry methods have been developed to sensitively detect minimal residual disease in multiple myeloma patients from plasma samples, allowing for dynamic monitoring and earlier detection of relapse compared to traditional methods.
3) Large-scale multi-omics studies incorporating data from various sources can provide a more holistic view of health and disease at both the individual and population levels, supporting personalized prevention and treatment approaches.
2022-09-08 ECPM Digital Biomarkers and AI, Basel, Alain van Gool.pdfAlain van Gool
Lecture for 150 pharma professionals to outline the potentials and things-to-do with digital biomarkers, as part of a ECPM training on digitization and AI in drug development.
2022-04-14 EuroMedLab, Munich, Alain van GoolAlain van Gool
Keynote lecture at the EuroMedLab 2021 providing an audience of clinical chemists and laboratory medicine scientists with advancements of multi-omics applications in personalized healthcare, and challenges that we need to solve as translational scientists.
2021 12-10 Amalia Science Day, Nijmegen, Alain van GoolAlain van Gool
This document discusses the use of omics technologies like genomics, proteomics, and glycoproteomics in pediatric healthcare. Specifically, it describes a study that used glycoproteomics to analyze blood samples from children with febrile illness to distinguish between viral and bacterial infections. The analysis identified glycoprotein biomarkers that could accurately classify 70-80% of samples as viral or bacterial. Integrating multiple omics data through machine learning approaches may provide a more comprehensive understanding of diseases and lead to personalized diagnosis and treatment.
2021 06-14 EATRIS-Plus summer school, Alain van GoolAlain van Gool
Introductory lecture for the 100 participant summer school of the EATRIS-Plus project, outlining personalized medicine, biomarker and multi-omics strategies and use cases.
2021 03-25 11th World Clinical Biomarkers & Companion Diagnostics, Alain van ...Alain van Gool
Closing keynote of a 3-day conference on clinical biomarkers and companion diagnostics, organised by Hanson Wade, outlining the power of omics approaches in healthcare and translation of inovations to impact.
2020 09-07 European Center Pharmaceutical Medicine course Biomarkers, Basel, ...Alain van Gool
Tutorial lecture on biomarkers for pharmaceutical industry R&D professionals, outlining status, potential and challenges of biomarkers in pharma, clinic and society.
2020 02-10 European Center Pharmaceutical Medicine course - biomarkers, Basel...Alain van Gool
This document discusses biomarkers and personalized healthcare. It begins with an overview of biomarkers in the pharmaceutical industry and how they are used from drug discovery through clinical trials. It then discusses biomarkers in academic research and healthcare, and how emerging digital biomarkers could enable personalized health monitoring. The presentation identifies some translational innovation gaps, and concludes with an outlook on how biomarkers and multi-omics approaches will continue to advance personalized diagnosis and therapies.
2019 10-14 2nd Int Congress on Precision Medicine, Munich, Alain van GoolAlain van Gool
Opening lecture at the 2nd International Congress on Precision Medicine in Munich, outlining progress in omics-based biomarkers for rare diseases, biomarker innovation gaps and multi-partner initiatives to bridge those gaps to applications. Also reviewed the highlights of our recently published Handbook of Biomarkers and Precision Medicine.
2019 09-23 COST CliniMARK summerschool, Spetses, Alain van GoolAlain van Gool
Opening lecture of the COST CliniMARK summer school 'Approaches for Biomarker Discovery and Validation'. Extensive introduction in biomarker approached used in pharmaceutical industry, academic research and clinical care, and society, combined with review of biomarker innovation gaps and outlook.
Lecture describing workflows and case studies from the Translational Metabolic Laboratory @Radboudumc how to translate x-omics biomarker signatures to clinical implementation. I also highlighted new developments to join forces in the Netherlands X-omics Initiative, United for Metabolic Disease and events/book launches in the next months.
Histololgy of Female Reproductive System.pptxAyeshaZaid1
Dive into an in-depth exploration of the histological structure of female reproductive system with this comprehensive lecture. Presented by Dr. Ayesha Irfan, Assistant Professor of Anatomy, this presentation covers the Gross anatomy and functional histology of the female reproductive organs. Ideal for students, educators, and anyone interested in medical science, this lecture provides clear explanations, detailed diagrams, and valuable insights into female reproductive system. Enhance your knowledge and understanding of this essential aspect of human biology.
Travel vaccination in Manchester offers comprehensive immunization services for individuals planning international trips. Expert healthcare providers administer vaccines tailored to your destination, ensuring you stay protected against various diseases. Conveniently located clinics and flexible appointment options make it easy to get the necessary shots before your journey. Stay healthy and travel with confidence by getting vaccinated in Manchester. Visit us: www.nxhealthcare.co.uk
share - Lions, tigers, AI and health misinformation, oh my!.pptxTina Purnat
• Pitfalls and pivots needed to use AI effectively in public health
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• Building trust with communities online and offline
• Equipping health professionals to address questions, concerns and health misinformation
• Assessing risk and mitigating harm from adverse health narratives in communities, health workforce and health system
Our backs are like superheroes, holding us up and helping us move around. But sometimes, even superheroes can get hurt. That’s where slip discs come in.
One health condition that is becoming more common day by day is diabetes.
According to research conducted by the National Family Health Survey of India, diabetic cases show a projection which might increase to 10.4% by 2030.
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
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Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
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Tests for analysis of different pharmaceutical.pptx
2015 11-26 Neuroinformatics and Personalized Health Care symposium, Nijmegen, Alain van Gool
1. Personalized Health(care):
more than just targeted medicines
Professor of Personalized Healthcare
Head Radboud Center for Proteomics, Glycomics
and Metabolomics
Coordinator Radboud Technology Centers
Senior Scientist Integrator Biomarkers
Prof Alain van Gool
Symposium Neuroinformatics and personalized health care
Nijmegen, 26 Nov 2015
2. My background in personalized health(care)
8 years academia (NL, UK)
(molecular mechanisms of disease)
13 years pharma (EU, USA, Asia)
(biomarkers, Omics)
4 years med school (NL)
(personalized healthcare, Omics, biomarkers)
4 years applied research institute (NL, EU)
(biomarkers, personalized health, nutrition)
A person / citizen / family man
(adventures in EU, USA, Asia)
1991-1996
(PhD)
1996-1998
(post-doc)
2009-2012
(visiting prof)
1999-2007 2007-2009 2009-2011
2011-now
2011-now (prof)
2 Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 2015
3. Source: Chakma, Journal of Young Investigators, 16, 2009
Principle of Personalized/Precision/Targeted Medicine
3
3
Molecular biomarkers as key drivers to select right patient for right drug
at right dose at right time: Companion Diagnostics
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 2015
4. Example: Personalized Medicine in melanoma
Key biomarkers:
Stratification: BRAFV600E DNA mutation assay
Mechanism: P-ERK
Cyclin-D1
Efficacy: Ki-67
18FDG-PET, CT
Clinical endpoint: progression-free survival (%)
{Source: Flaherty et al, NEJM 2010}{Source: Chapman et al, NEJM 2011}
4 Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 2015
5. Emerging companion diagnostics
Good examples personalized medicine in Oncology:
• Cyp450, Her2/neu, BRCA, BRAF, EGFR, EML4/ALK, etc
• Issue with drug resistancy in several solid tumors
Emerging, also beyond the oncology field:
• Volker: Intestinal surgery → XIAP → Cord blood
• Beery twins: Cerebral palsy → SPR → Diet 5HTP
• Wartman: Leukemia → FLT3 → Sunitinib
• Gilbert: Healthy → BRCA → Mas/Ovarectomy
• Snyder: T2Diabetes → GCKR, KCNJ11 → Diet, exercise
• Lauerman: Scotoma, leg → JAK2 → Aspirin
• Bradfield: Healthy → CDH1 → Gastrectomy
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 20155
6. Companion diagnostics in current drug labels
Metabolism
Efficacy or
safety
Source: www.fda.gov (June 2013)
= molecular biomarker that indicates the right patient for right drug at
right dose at right time
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 20156
7. Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 20157
Rational selection of best targets and biomarkers works
The 5R’s assessment:
• Right Target
• Right Tissue
• Right Safety
• Right Patients
• Right Commercial Potential
10. People are more than linear pathways
Source: Barabási 2007 NEJM 357; 4}
• People are different
• Different networks and influences
• Different risk factors
• Different preferences
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201510
11. Personalized health(care) in a systems view
11
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201511
12. Societal need in efficient personalized health(care)
Source: prof Jan Kremer
Towards cost effective care, less cure
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201512
13. Personal need in efficient personalized health(care)
It’s personal !
‘I want to stay healthy.’
‘If not, how do I get healthy?’
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201513
14. A changing world in Personalized Medicine@ USA
“The term "personalized medicine" is
often described as providing "the
right patient with the right drug at
the right dose at the right time."
More broadly, "personalized
medicine" may be thought of as the
tailoring of medical treatment to the
individual characteristics, needs, and
preferences of a patient during all
stages of care, including prevention,
diagnosis, treatment, and follow-up.”
(FDA, October 2013)
14
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201514
15. Personalized Healthcare @ Radboudumc
People are different Stratification by multilevel diagnosis
+Patient’s preference of treatment
Exchange experiences in
care communities Select personalized therapy
Population
Man
Molecule
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201515
16. Exponential developments in biomarker technologies
• Next generation sequencing
• DNA, RNA
• Risk analysis and therapy selection
• Mass spectrometry
• Proteins, metabolites
• Monitoring of disease and treatment effects
• Imaging
• Non invasive images, real time
• Spatial view of intact organs and organisms
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201516
17. Mass spectrometry
• Example: Glycoproteomics in plasma
• Detection of ~12.000 unique deconvoluted monoisotopic masses
per single analysis (> 50% are glycopeptides)
500
1000
1500
2000
m/z
5 10 15 20 25 30 35 40 Time [min]
Proof of principle study:
Monique van Scherpenzeel, Dirk Lefeber, Hans Wessels, Alain van Gool
Translational Metabolic Laboratory, Radboudumc, unpublished data
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201517
19. 19
New data !
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201519
20.
21.
22. Key aspects of personalized health(care)
‘I want to stay healthy. If not, how do I get healthy?’
1. What to measure?
2. How much can it change?
3. What should be the follow-up for me?
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201522
23. Personalized Health(care) model
Personalized
Intervention
of patients-like-me
Risk profiles
of persons-like-me
Big
Biomarker
Data
Molecular
Non-molecular
Environment
…
HomeostasisAllostasisDisease
Time
Disease
Health
Selfmonitoring
Adapted from Jan van der Greef, TNO (2013)
Personal profile
Personalized
Participatory
Pre-emptive
Personalized health
Personalized medicine
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201523
24. The route to Personalized Health(care)
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201524
25. Analogy: TOMTOM
GPS to a location
Amsterdam
Traffic jam
Amsterdam
Route 1 Route 2
= Default Traffic jam near Utrecht Alternative route
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201525
26. Personalized Health(care) model
GPS to health
Health
Route 1 Route 2
= Default
First signs of
disease risk
Alternative route
Now
Disease risk
Health
Now
Health
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201526
27. Translation is key in Personalized Healthcare !
Personal profile data
Knowledge
Understanding
Decision
Action
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201527
28. Translation is key in Personalized Healthcare !
“I’m afraid you’re
suffering from an
increased IL-1β and
an aberrant miR843
expression”
Adapted from:
?
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201528
29. Shared decision making
Treatment options
Pro’sCon’s
Select personalized therapy
Example from Prostate cancer patient guide
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201529
30. Mind the Biomarker innovation gaps
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
Gap 3
• Too much biomarker discovery
• Too little development to application
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201530
31. Biomarker innovation gaps: some numbers
5 biomarkers/
working day
1 biomarker/
1-3 years
1 biomarker/
3-10 years
?
Eg Biomarkers in time: Prostate cancer
May 2011: n= 2,231 biomarkers
Nov 2012: n= 6,562 biomarkers
Oct 2013: n= 8,358 biomarkers
Nov 2014: n= 10,350 biomarkers
Oct 2015: n = 11,856 biomarkers
Discovery Clinical
validation/confirmation
Diagnostic
test
Number of
biomarkers
Gap 1
Gap 2
Gap 3
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201531
32. Most important in Personalized Health(care):
Focus on the end user: the patient / citizen
32
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201532
33. Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201533
34. Acknowledgements
Ron Wevers
Jolein Gloerich
Hans Wessels
Monique Scherpenzeel
Dirk Lefeber
Leo Kluijtmans
Lucien Engelen
Nathalie Bovy
Paul Smits
Maroeska Rovers
Bas Bloem
and many others
www.radboudumc.nl/personalizedhealthcare
www.radboudumc.nl/research/technologycenters
www.radboudresearchfacilities.nl
alain.vangool@tno.nl
alain.vangool@radboudumc.nl
www.linkedIn.com
www.slideshare.net/alainvangool
Many collaborators
Jan van der Greef
Ben van Ommen
Bas Kremer
Lars Verschuren
Ivana Bobeldijk
Marjan van Erk
Carina de Jongh
Peter van Dijken
Peter Wielinga
Robert Kleemann
Suzan Wopereis
and many others And funders
CarTarDis
Alain van Gool, Workshop Neuroinformatics and personalized health care , Nijmegen, 26 Nov 201534