GMOs are ‘substantially equivalent’ to conventional foods. Should they face reduced regulations?

If there is a single concept that drives much of the divide in the GMO debate, it’s substantial equivalence. Having different understandings or misunderstandings of the concept leads to rancor, distrust and talking past each other. Proponents see it as a common sense way of determining if heightened regulatory scrutiny for a new product is warranted or unnecessary. Critics of genetic engineering often see it as some sort of trick — a sleight of hand or legalistic loophole. They ask how something can be so novel that on one hand, it merits the legal protection of a patent monopoly, and then on the other hand, the FDA can declare it to be substantially equivalent to its parent variety or breed. That suspicious and often paranoid take is nearly always based on misunderstandings of the concept of substantial equivalence and how patents work.

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Medacs Global Group is one of the leading international healthcare staffing and services companies. Operating under a variety of brands including Medacs Healthcare, Global Medics, Doctors-on-call, Fast Response Healthcare and Litmus Solutions, we provide healthcare recruitment, managed services, occupational health, social care and home care services.

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Top 3 Biotech Clinical Data Management Trends to Watch in 2022

Article | July 14, 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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MedTech

Expansion of BioPharma: Opportunities and Investments

Article | July 11, 2022

Biopharmaceutical innovations are among the most ingenious and refined achievements of modern medical science. New concepts, techniques, and therapies are emerging, such as the cell therapy Provenge, which can be used to treat cancer, and gene therapies, which provide even more amazing promises of disease remission and regenerative medicine. In addition, the COVID-19 pandemic has caused a huge boom in the pharmaceutical industry. This is because more and more attention is being paid to increasing manufacturing capacity and starting new research on drug development. Biopharma: Leading the Way in the Pharma Sector In the past couple of years, the biopharmaceutical sector has deepened its roots across the medical and pharmaceutical industries, on account of the transformation of pharmaceutical companies towards biotechnology, creating opportunities for growth. Also, growing advancements in technologies such as 3D bioprinting, biosensors, and gene editing, along with the integration of advanced artificial intelligence and virtual and augmented reality are estimated to further create prospects for growth. According to a study, the biopharmaceutical sector makes nearly $163 billion around the world and grows by more than 8% each year, which is twice as fast as the traditional pharma sector. Massive Investments Directed Towards Biopharma Investing in biotech research and development (R&D) has yielded better returns than the pharma industry average. Hence, a number of pharmaceutical companies are shifting their presence toward biopharma to capitalize on the upcoming opportunities by investing in and expanding their biotechnology infrastructure. For instance, Thermo Fisher Scientific Inc., an American manufacturer of scientific instrumentation, reagents and consumables, and software services, announced an investment of $97 million to expand its bioanalytical laboratory operations into three new locations in the U.S. With this investment, the company will add 150,000 square feet of scientific workspace and install the most advanced drug development technologies to produce life-changing medicines for patients in need.

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MedTech

Next-Gen Gene Therapy to Counter Complex Diseases

Article | July 16, 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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Industrial Impact

AI and Biotechnology: The Future of Healthcare Industry

Article | January 20, 2021

Artificial intelligence has grasped the foundation in biotech. It can have the most innovative impact on biotechnology. AI has already established its presence in our day-to-day life. AI has made the existence of self-driving cars possible. Likewise, the benefits and quality that it can contribute to biotech can also be felt. With AI, bio technicians will be able to enhance virtual screening, overlook preliminary datasets from clinics, and decipher an enormous amount of information. It can also help in improving the medication process by gathering and analyzing every bit of information. The Significance of AI in Biotechnology In the past few years, the application of artificial intelligence in the biotechnology industry has shifted from being sci-fi to sci-fact. A vast number of biotech companies like Deep Genomics are adopting AI for making data-driven decisions and use analytics tools to work efficiently. Unlike the AI robots in sci-fi that are ready to take over the world. AI designed for biotech has been designed to solve certain problems or complete a bunch of tasks by using automated algorithms. The aim of AI technology for biotech is to collect insights along with hidden patterns from large amounts of data. All the different industries of biotech including agriculture, animal, medical, industrial, and bioinformatics are gradually being affected by artificial intelligence. Moreover, the biotech industry is realizing that AI enables them some of the important strength to their business, including: Expanding accessibility Cost-effectiveness Critical predictions Efficient decision-making Research centers like PwC have also estimated output of $15.7 trillion by 2030 solely with AI contribution in industries. A survey revealed that about 44% of life science experts are using AI for R&D activities, as well. Use of AI in Biotechnology Altering Biomedical and Clinical Data So far the most developed use of AI is its ability to read voluminous data records and interpret them. It can prove to be a life-save for bio technicians who would have to examine that much data from research publications by themselves for the validation of their hypothesis. With the help of AI, clinical studies of patients will also become easier as all the examination reports and prescriptions will be stored in one place for cross-reference. Furthermore, it will also help in blending and fetching data into usable formats for analysis. Test Result Prediction Through trial and error, AI along with machine learning can help in predicting the response of the patient to certain drugs to provide more effective outcomes. Drug Design & Discovery AI plays a vital role whether it’s designing a new molecule or identifying new biological targets. It helps in identifying and validating drugs. It reduces the cost and time spent on the entire drug trial process and reaches the market. Personalized Medications for Rare Diseases With the combination of body scan results, patients’ body and analytics, AI can also help in detecting dangerous diseases at an early stage. Improving Process of Manufacturing To improve the process of manufacturing in biotechnology, AI offers a wide range of opportunities. It controls quality, reduces wastage, improves useability, and minimizes the designing time. Moving Towards AI-Enhanced Biotech Future Ever since the concept of artificial intelligence has arrived, being curious by nature, humans have started working towards achieving this goal. It has been growing at a fast pace while showing unbelievable growth and achievements at times. In comparison to the traditional methods used in the biotechnology industry, AI-based methods seem more reliable and accurate. In the upcoming years, it will show its success by improving the quality of health people have. You can also develop your AI-based application or know more about it by taking IT consultations.

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Spotlight

Medacs Global Group

Medacs Global Group is one of the leading international healthcare staffing and services companies. Operating under a variety of brands including Medacs Healthcare, Global Medics, Doctors-on-call, Fast Response Healthcare and Litmus Solutions, we provide healthcare recruitment, managed services, occupational health, social care and home care services.

Related News

Biotech companies launch new website for GMO conversations

Dow AgroSciences | June 29, 2013

GMO Answers is a new website launched by The Council for Biotechnology Information, which includes BASF, Bayer CropScience, Dow AgroSciences, DuPont, Monsanto and Syngenta. The new initiative is aimed at answering questions from the public about GMOs and how food is produced.

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Biotech companies launch new website for GMO conversations

Dow AgroSciences | June 29, 2013

GMO Answers is a new website launched by The Council for Biotechnology Information, which includes BASF, Bayer CropScience, Dow AgroSciences, DuPont, Monsanto and Syngenta. The new initiative is aimed at answering questions from the public about GMOs and how food is produced.

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