Merging With Machines: A Look at Emerging Neuroscience Technologies

Billionaire entrepreneur and technophile Elon Musk is just one of the prominent futurists echoing the sentiment that we are on the verge of a full merger with machines. “It’s increasingly hard to tell where I end and where the computer begins,” states historian, professor, and New York Times bestselling author Yuval Noah Harari at his keynote address at the Fast Company European Innovation Festival. “In the future, it is likely that the smartphone will not be separated from you at all. It may be embedded in our body or brain, constantly scanning your biometric data and your emotions.”

Spotlight

Cambridge Epigenetix

Cambridge Epigenetix Ltd is commercializing a novel technology that pioneers quantitative single-base resolution sequencing of the methylated bases 5-hmC and 5-mC leading to substantially more accurate determination of the methylated status of genomic DNA with relevance in research, pharmaceutical discovery and diagnostics.

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MedTech

Next-Gen Gene Therapy to Counter Complex Diseases

Article | July 20, 2022

Gene therapy has historically been used to treat disorders with in-depth knowledge caused by a single genetic mutation. Thanks to the introduction of new generation technologies, the potential of gene therapy is expanding tAo treat diseases that were previously untreatable. Evolution of Gene Therapy One of the major success stories of the twenty-first century has been gene therapy. However, it has not been the same in the past. The field's journey to this point has been long and mostly difficult, with both tragedy and triumph along the way. Initially, genetic disorders were thought to be untreatable and permanently carved into the genomes of individuals unfortunate enough to be born with them. But due to the constant technological advancement and research activities, gene therapy now has the potential to treat various genetic mutation-causing diseases with its ability to insert a new copy and replace faulty genes. Gene Therapy is Finding New Roads in the Medical Sector Gene therapy can help researchers treat a variety of conditions that fall under the general heading of epilepsy, instead of only focusing on a particular kind of disorder brought on by a genetic mutation. Following are some of the domains transformed by gene therapy. Neurology – Gene therapy can be used for the treatment of seizures by directly injecting it into the area causing an uncontrolled electrical disturbance in the brain. Furthermore, by using DNA sequences known as promoters, gene therapy can be restricted to specific neurons within that area. Ophthalmology – Genetic conditions such as blindness can be caused due to the mutation of any gene out of over 200 and resulting in progressive vision loss in children. With advanced gene therapies such as optogenetics, lost photoreceptor function can be transferred to the retinal cells, which are responsible for relaying visual information to the brain. This might give patients the ability to navigate in an unknown environment with a certain level of autonomy. The Future of Gene Therapy The news surrounding gene therapy has been largely favorable over the past few years, with treatment after treatment obtaining regulatory approvals, successful clinical trials, and garnering significant funds to begin development. With more than 1,000 clinical trials presently underway, the long-awaited gene therapy revolution might finally be here.

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MedTech

Top 3 Biotech Clinical Data Management Trends to Watch in 2022

Article | July 13, 2022

Introduction The administration of medical records and data has advanced significantly during the past few decades. Clinical data management, which was once only a small subset of biotech research organizations, has now developed into a mission-critical, specialized unit. In the late 1990s, electronic data capture (EDC) began to alter the traditional function of clinical data management. After that, the data configuration and management of data queries for the EDC system fell under the purview of clinical data management services. Today, clinical data management is not only responsible for managing the clinical data configuration and data queries but also developing and implementing data administration plans, ensuring data accuracy and completeness, and maintaining optimum data security. In recent years, as digital technologies have gained acceptance around the globe, data has become a vital aspect in decision-making across numerous industries, and the life sciences and biotechnology sectors are no exception. Using data has provided granular insights to biotech organizations, assisting them in creating breakthroughs in drug development and medical research and signifying the importance of clinical trial management systems in these medical verticals. The Biggest Biotech Clinical Data Management Trends to Know About Today The future of clinical data management is contingent upon the implementation of systems and regulations. It is imperative for all organizations participating in a medical or life science trial to have transparent rules in place for sharing and retaining patient data. Also, there is a need to have a standardized format for maintaining these records and documents related to trials. This assists biotech organizations in reducing the chances of ambiguity regarding who owns what kind of data or paperwork at any given time. Over the past couple of years, the focus of the life science and biotechnology industries has shifted towards developing more effective medications and therapies, implementing personalized treatment, and finding cures for diseases such as cancer and AIDS. In response to this, a substantial rise in the number of clinical trials is being witnessed globally. As the number of clinical trials continues to accelerate, the spending on these trials rises as well. In response to this, the worldwide cost of conducting clinical trials is anticipated to reach US$ 49.80 billion in 2022. With the transition of the world from traditional to digital, medical professionals and biotech businesses are increasingly shifting towards adopting high-tech and reliable clinical trial management systems for various applications, starting from diagnosis and clinical trials to patient data documentation. But, what are the future trends in biotechnology clinical data management? Let’s discuss. Cloud-Based Clinical Metadata Repositories Automation is emerging as a new frontier in the biotech clinical data management domain, along with other innovative technologies such as artificial intelligence and machine learning. Because of this, life science establishments are witnessing a huge shift from paper-based documentation toward data-based documentation, which is creating mountains of research, compliance, and clinical data. The growing demand for new and more effective medications and drugs is augmenting the need to expedite clinical trials. This is resulting in an increased number of initiatives aimed at optimizing clinical trial processes to prepare and launch successful trials. However, pharmaceutical and biotechnology laboratories are encountering several challenges in collecting, managing, and analyzing metadata due to its complexities. So, what is the best solution to this problem? The answer to this is cloud-based clinical metadata repositories. Clinical research facilities are leveraging advanced, all-in-one, cloud-based clinical metadata repositories to assist them in centralizing and managing metadata; increasing metadata quality, consistency, and accuracy; and speeding up clinical trial management, documentation, and compliance processes. Shift Towards Digital Solutions Electronic Case Report Form Adequate research and accurate data are crucial for a clinical trial to succeed. Whether developing new drugs, medication, or therapies; conducting life science research; or studying the latest clinical trial systems, it is best to use electronic solutions as it reduces the room for mistakes during the transition of clinical data from paper-based format. Realizing this, biotech organizations are shifting towards using electronic case report forms to speed up record retrieval, improve record security, and cut down on operational costs associated with running clinical trials. The electronic case report form assists in lowering the failure rate of the clinical trial, enhancing efficiency, and optimizing security along with improving clinical trial documentation and productivity, further driving its adoption in the medical space. Electronic Clinical Outcome Assessment Electronic clinical outcome assessment is surfacing as one of the fast-growing future trends in biotechnology. It allows clinical trial facilities to automate data entry and improve the reliability of the collected information. The technology enables clinical trial institutions to automatically record patient-provided information about side effects, symptoms, drug timing, and other aspects during the clinical trial for increased precision. It also helps these institutions analyze the results of medication or therapy in clinical trials and lets clinical researchers use medical technologies like biosensor-enabled devices, self-service applications, and medical wearables for evaluation. Hence, biotech clinical facilities are increasingly deploying advanced electronic clinical outcome assessment systems to ensure adherence to protocols and regulations. Clinical Trial Customization The success of a new drug is determined by numerous factors other than its effectiveness, safety, and creativity of its developers, such as a successful clinical trial. Each clinical trial involves a number of decision-making points, and one wrong choice in any of these aspects can jeopardize the success of the entire endeavor. A crucial component of making well-informed decisions is data management, which is a part of clinical study as a whole. Clinical trial customization is emerging as one of the most prominent biotech clinical trial management trends. Every clinical trial is unique and needs a tailored approach to be successful. With the emergence of the trend of personalized treatment around the globe, biotech and pharmaceutical organizations are adopting innovative customized clinical trial management solutions to accelerate the pace of clinical trials and approvals. This is giving clinical researchers innovative ways to come up with new medicines for patients and streamline the clinical data as per the requirements for faster approvals. What Are the Key Clinical Data Management Challenges Faced by Biotech Companies? Groundbreaking medical interventions are of no use without reliable, accurate, and extensive clinical trial data. Without the data, biotech and pharmaceutical companies will not be able to provide the assurance of safety and efficacy required to bring the medication to market. Regulatory bodies such as the Food and Drug Administration (FDA), the Medicines and Healthcare Products Regulatory Agency (MHRA), and others are putting stricter rules in place to ensure the quality of clinical data. In addition, the fast-changing clinical development environment is creating more obstacles for biotech and medical spaces to ensure the accuracy, standard, and completeness of the clinical trial data. Hence, clinical teams are spending valuable time cleaning up data instead of analyzing it. Time spent trying to figure out issues with clinical trial data is detrimental and expensive but also mission-critical. This is because a small issue in the data can lead to numerous consequences, from small delays to calamitous setbacks, making it necessary to rerun clinical trials. This problem will only get more challenging to address as the volume of data and the types of data sources continue to grow. Here are some of the major clinical data management challenges that biotech firms encounter Standardization of Clinical Metadata Stringent Regulatory Compliance Increased Clinical Trial Complexity Mid-Study Changes Why Are Clinical Data Management Systems Garnering Popularity in the Biotech Industry? With the changing regulatory and clinical landscape, biotech and pharmaceutical companies are facing several obstacles in the management of clinical data and clinical trials. In addition, regulatory agencies are moving toward integrated electronic systems, which is making it more and more important for clinical laboratories to change the format of their submissions. Because of this, several biotech clinical labs are focusing on adopting innovative laboratory solutions, such as biotech clinical data management systems, to meet the need for standardized data inputs and replace all manual ways of working with electronic systems. A clinical data management system establishes the framework for error-free data collection and high-quality data submission, resulting in speedier drug discovery and shorter time-to-market. These solutions are gaining huge traction among biotech and pharmaceutical companies, owing to their ability to effectively manage clinical data, accelerate clinical trials, and ensure compliance. Let’s see some of the features of biotech clinical data management software that are most sought after by life-science companies Controlled, standardized data repository. Centralized data analysis and administration. Reduced operational expenditures for clinical data processes. Enhanced process effectiveness. Superior submission quality Compliance with predefined standards. Clinical Data Management Systems: The Future The role of clinical data management systems is evolving at a rapid pace as the life science and medical industries continue to incorporate digital solutions for diverse operations. These systems are being used in a variety of biotech clinical settings, ranging from clinical data compliance to data science and analytics, to help them analyze large and growing volumes of clinical data. Hence, a number of high-tech medical companies are aiming at integrating innovative technologies, such as artificial intelligence and machine learning, into clinical data management software to automate clinical data management tasks, improve clinical data submission, and enhance data quality. These new biotech clinical management technologies are anticipated to help life science laboratories gain a better understanding of diseases and speed up clinical trials in the coming years. FAQ What is a clinical data management system? A clinical data management system (CDMS) is a tool used in clinical research to track, record, and manage clinical trial data across medical establishments such as biotech laboratories. What are the key functions of the biotech clinical data management system? Some of the key functions of biotech clinical data management system are Documentation of Protocols and Regulations Patient Recruitment Real-time Clinical Study Analytics Reporting Investigator Relationship Management Electronic Visit Report Why is a clinical data management system needed for clinical trials today? A clinical data management system helps shorten the time from drug development to marketing by assisting in the collection of high-quality, statistically sound, and accurate data from clinical trials.

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Research

2022 U.S. Market Research Report with COVID-19 Forecasts2

Article | July 11, 2022

The global biotechnology market is expected to grow at a compound annual growth rate (CAGR) of 13.9 percent from 2022 to 2030, with a value estimated at USD 1,023.92 billion in 2021. The market is being propelled by strong government support in the form of initiatives aimed at modernizing the regulatory framework, improving approval processes and reimbursement policies, and standardizing clinical studies. The growing presence of personalized medicine and an increasing number of orphan drug formulations are opening up new avenues for biotechnology applications and driving the influx of emerging and innovative biotechnology companies, which is driving market revenue even further. The 2022 Biotech Research and Development Market Research Report is one of the most comprehensive and in-depth assessments of the industry in the United States, containing over 100 data sets spanning the years 2013 to 2026. This Kentley Insights report contains historical and forecasted market size, product lines, profitability, financial ratios, BCG matrix, state statistics, operating expense details, organizational breakdown, consolidation analysis, employee productivity, price inflation, pay bands for the top 20 industry jobs, trend analysis and forecasts on companies, locations, employees, payroll, and much more. Companies in the Biotech Research and Development industry are primarily engaged in biotechnology research and experimental development. Biotechnology research and development entails the investigation of the use of microorganisms and cellular and bimolecular processes to create or modify living or non-living materials. This biotechnology research and development may result in the development of new biotechnology processes or prototypes of new or genetically altered products that can be replicated, used, or implemented by various industries. This report was created using the findings of extensive business surveys and econometrics. The professionals follow reports with accurate and apt information on market sizing, benchmarking, strategic planning, due diligence, cost-cutting, planning, understanding industry dynamics, forecasting, streamlining, gap analysis, and other ana

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Wisconsin biotech companies could play key roles in long-term economic recovery from COVID-19 pandemic

Article | April 19, 2020

Whether it’s called a modern “Manhattan Project” or a medical moon shot, the concept of long-term economic recovery rests on how confident people are they won’t risk serious illness by venturing forth in public again. Wisconsin stands to be a significant part of such an undertaking, whatever it’s called. The shorter-term debate is well under way over the gradual lifting of COVID-19 emergency rules, such as the now-extended “safer-at-home” order in Wisconsin. At least a dozen states, including regional coalitions on the East and West coasts, are exploring next steps as they seek to balance responses to the virus with calls for reopening the economy, at least, in part. Wisconsin’s ability to shape longer-term responses will come from private and public resources, which range from companies engaged in production of diagnostics.

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Spotlight

Cambridge Epigenetix

Cambridge Epigenetix Ltd is commercializing a novel technology that pioneers quantitative single-base resolution sequencing of the methylated bases 5-hmC and 5-mC leading to substantially more accurate determination of the methylated status of genomic DNA with relevance in research, pharmaceutical discovery and diagnostics.

Related News

Neurocrine Biosciences and Xenon Launch Up-to-$1.7B Epilepsy, Neuroscience Collaboration

GEN | December 02, 2019

Neurocrine Biosciences has agreed to exclusively license and co-develop Xenon Pharmaceuticals’ Phase I epilepsy candidate XEN901 as a treatment for children—as well as develop three preclinical compounds, the companies said today—through a collaboration that could generate up to $1.7 billion for Xenon. XEN901 is designed as a highly selective Nav1.6 sodium channel inhibitor being developed to treat children with SCN8A developmental and epileptic encephalopathy (SCN8A-DEE) and other potential indications, including adult focal epilepsy. Xenon has completed a Phase I trial of a powder-in-capsule formulation of XEN901 in healthy adults. However, Xenon has also developed a pediatric-specific, granule formulation of XEN901, and has completed juvenile toxicology studies intended to support pediatric development of the drug candidate. “With its proven expertise in developing and commercializing treatments for neurological disorders, we believe Neurocrine Biosciences is an ideal partner to maximize the potential value of XEN901 for patients,” Xenon CEO Simon Pimstone, MD, PhD, FRCPC, said in a statement.

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Machine Learning Harnessed To Build Map of the Connectome

Technology Networks | November 08, 2019

The brain is considered to be one of the most complex systems in existence. And while significant headway has been made to understand it, we tend to generate more questions than answers. But now a research team led by Kyoto University has developed a machine learning model that allows scientists to reconstruct neuronal circuitry by measuring signals from the neurons themselves. The model has the potential to elucidate the difference in neuronal computation in different brain regions. To comprehend the brain, we must look at the neurons that construct it. Our entire world of perception runs across these billions of cells in our head. And that is compounded by the exponentially larger number of connections -- known as synapses -- between them, making the path to our understanding a challenge. Shigeru Shinomoto from Kyoto University's School of Science, who headed the project, explains that although it is possible to record the activity of individual neurons in the brain -- and that number has increased dramatically over the last decade -- it is still a challenge to map out how each of these cells connects to each other.

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UK Scientists Speed up Brain Cancer Diagnosis with AI

Labiotech.eu | November 05, 2019

A technique combining a blood test with artificial intelligence (AI), developed by the UK company ClinSpec Diagnostics, could help to prioritize which patients need to be scanned for brain cancer. A team led by researchers at the University of Strathclyde and the University of Edinburgh, UK, trialed the technology on blood samples from 400 people suspected of having brain tumors. The researchers used an existing technique called infrared spectroscopy to screen 20,000 chemicals in their blood, and then used AI to identify the chemicals that signal a brain tumor. The test correctly identified 82% of the patients that would go on to be diagnosed with brain cancer. Patients flagged with this brain cancer test can be prioritized for confirmatory brain scans, and their diagnosis might take just two weeks. In current practice, it’s difficult to diagnose tumors from patients’ symptoms, and the process can take up to two months, with multiple visits to the doctor. The blood test is being developed by Brennan’s collaborator, the UK company ClinSpec Diagnostics. While other groups are working on cancer tests using infrared spectroscopy and AI, ClinSpec’s test is the most advanced, according to Brennan.

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Neurocrine Biosciences and Xenon Launch Up-to-$1.7B Epilepsy, Neuroscience Collaboration

GEN | December 02, 2019

Neurocrine Biosciences has agreed to exclusively license and co-develop Xenon Pharmaceuticals’ Phase I epilepsy candidate XEN901 as a treatment for children—as well as develop three preclinical compounds, the companies said today—through a collaboration that could generate up to $1.7 billion for Xenon. XEN901 is designed as a highly selective Nav1.6 sodium channel inhibitor being developed to treat children with SCN8A developmental and epileptic encephalopathy (SCN8A-DEE) and other potential indications, including adult focal epilepsy. Xenon has completed a Phase I trial of a powder-in-capsule formulation of XEN901 in healthy adults. However, Xenon has also developed a pediatric-specific, granule formulation of XEN901, and has completed juvenile toxicology studies intended to support pediatric development of the drug candidate. “With its proven expertise in developing and commercializing treatments for neurological disorders, we believe Neurocrine Biosciences is an ideal partner to maximize the potential value of XEN901 for patients,” Xenon CEO Simon Pimstone, MD, PhD, FRCPC, said in a statement.

Read More

Machine Learning Harnessed To Build Map of the Connectome

Technology Networks | November 08, 2019

The brain is considered to be one of the most complex systems in existence. And while significant headway has been made to understand it, we tend to generate more questions than answers. But now a research team led by Kyoto University has developed a machine learning model that allows scientists to reconstruct neuronal circuitry by measuring signals from the neurons themselves. The model has the potential to elucidate the difference in neuronal computation in different brain regions. To comprehend the brain, we must look at the neurons that construct it. Our entire world of perception runs across these billions of cells in our head. And that is compounded by the exponentially larger number of connections -- known as synapses -- between them, making the path to our understanding a challenge. Shigeru Shinomoto from Kyoto University's School of Science, who headed the project, explains that although it is possible to record the activity of individual neurons in the brain -- and that number has increased dramatically over the last decade -- it is still a challenge to map out how each of these cells connects to each other.

Read More

UK Scientists Speed up Brain Cancer Diagnosis with AI

Labiotech.eu | November 05, 2019

A technique combining a blood test with artificial intelligence (AI), developed by the UK company ClinSpec Diagnostics, could help to prioritize which patients need to be scanned for brain cancer. A team led by researchers at the University of Strathclyde and the University of Edinburgh, UK, trialed the technology on blood samples from 400 people suspected of having brain tumors. The researchers used an existing technique called infrared spectroscopy to screen 20,000 chemicals in their blood, and then used AI to identify the chemicals that signal a brain tumor. The test correctly identified 82% of the patients that would go on to be diagnosed with brain cancer. Patients flagged with this brain cancer test can be prioritized for confirmatory brain scans, and their diagnosis might take just two weeks. In current practice, it’s difficult to diagnose tumors from patients’ symptoms, and the process can take up to two months, with multiple visits to the doctor. The blood test is being developed by Brennan’s collaborator, the UK company ClinSpec Diagnostics. While other groups are working on cancer tests using infrared spectroscopy and AI, ClinSpec’s test is the most advanced, according to Brennan.

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