MedTech
Article | July 16, 2022
Genomics is an interdisciplinary field of biology emphasizing the structure, editing, evolution, function, and mapping of genomes. It is creating deeper inroads across the precision health domain with the increasing introduction of advanced technologies such as quantum simulation, next-generation sequencing (NGS), and precise genome manipulation.
As precision health focuses on providing the proper intervention to the right patient at the right time, genomics increasingly finds applications in human and pathogen genome sequencing in clinical and research spaces.
Rising Hereditary Diseases Burden Paving the Way for Genomics in Precision Health
In the last few years, a significant surge in the prevalence of diseases and ailments such as diabetes, obesity, baldness, and others has been witnessed across the globe. A history of family members with chronic diseases, such as cancer, diabetes, high blood pressure, hearing issues, and heart disease, can sometimes continue into the next generation.
Hence, the study of genes is extensively being conducted for predicting health risks and early treatment of these diseases. It also finds use in CRISPR-based diagnostics and the preparation of precision medication for the individual.
In addition, ongoing advancements in genomics are making it possible to identify different genetic traits that persuade people to more widespread diseases and health problems.
The Emergence of Genomics Improves Disease Understanding
Genomics refers to the study of the complete genetic makeup of a cell or organism. Increasing scientific research in the area substantially contributes to increasing knowledge about the human genome and assists in improving the ability to understand disease etiology, risk, diagnosis, treatment, and prevention. On account of these improvements, innovative genomic technologies and tools are being developed to enable better precision health not only for the individual but for various regional populations as well.
The Way Forward
With growing preference for personalized medicine and an increasing need for more accurate pathogen detection and diagnostics, genomics is gaining huge popularity across the precision health domain.
Also, increasing research activities for developing novel high-precision therapeutics and rising importance of gene study in the prevention, diagnosis, and management of infectious and genetic diseases will further pave the way for genomics in the forthcoming years.
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Medical
Article | July 14, 2022
Introduction
Recent developments in the bioengineering of monoclonal antibodies (mAbs) have revolutionized the treatment of numerous rheumatic and immunological disorders.
Currently, several immunological disorders are successfully being targeted and treated using innovative medical techniques such as immunotherapy. Leading companies are increasingly investing in research activities to expand the usage and application of immunology for the treatment of various infectious diseases, including multiple sclerosis, inflammatory bowel disorders, lupus, and psoriasis, leading companies are increasingly investing in research activities.
Today, the efforts of researchers in immunology, with a long history of study and research, have borne fruit, as bioengineered mAbs are now being employed in clinical practices.
Accelerating Investments: Paving the Way for Immunology
The increasing prevalence of infectious diseases, cancer, and immune-mediated inflammatory disorders (IMIDs) is raising the need for more precise classification and an in-depth understanding of the pathology underlying these ailments.
Numerous leaders in the biotechnology domain are thus focusing on undertaking numerous strategies, such as new facility launches and collaborations, to address the need by finding deeper inroads into immunology and its use in disease treatments.
For instance, in 2022, the University of Texas MD Anderson Cancer Center announced the launch of a visionary research and innovation hub, the James P. Allison Institute, to find new roads in immunotherapy, develop new treatments, and foster groundbreaking science.
These developments will result in better diagnosis through the use of selective biomarkers, and early detection of fatal diseases and their treatment, which will prevent complications from happening. Also, the identification of high-risk populations through a deeper understanding of genetic and environmental factors can assist in the prevention of disease through immunotherapy.
The Way Forward
Immunology has led to the development of biotechnology, making it possible to develop novel drugs and vaccines, as well as diagnostic tests, that can be used to prevent, diagnose, and treat a wide range of autoimmune, infectious, and cancerous diseases.
With the rapid advancement in technology and the integration of artificial intelligence, immunology is finding its way into an array of domains and industries, encompassing several research areas including medicine, pharmaceuticals, agriculture, and space.
Today, not only researchers but also leading biotech and pharmaceutical companies have recognized that conventional therapies with pharmaceutical and chemical products are being replaced by products derived from immunology. This is because they work well for health problems, are environmentally friendly, and are also emerging as a wealth-generating business in the medical field.
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MedTech
Article | July 12, 2022
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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MedTech
Article | October 7, 2022
Introduction
The medical and life-science industries are experiencing a robust transformation with the increasing prevalence of various types of diseases, including infectious diseases, chronic disorders, and acute conditions around the world. As a result, a significant rise in demand for more effective therapeutic drugs and bionics is being witnessed, leading to a swift increase in the number of clinical trials.
For a successful trial, it is important for biotech companies to ensure the data submitted to regulatory bodies regarding clinical trials is accurate, reliable, and definitive from an ethical point of view. A reliable clinical trial management system plays a vital role in collecting, monitoring, and managing clinical data. The availability of high-quality clinical data also helps clinical research institutions make efficient treatment decisions and provide proper patient care.
Hence, a number of biotech companies and research organizations are focusing on leveraging innovative clinical trial management solutions to handle a large amount of data, particularly in multi-center trials, and generate reliable, high-quality, and statistically sound data from clinical trials. However, selecting the most appropriate and reliable clinical trial management system is vital for the clinical trial's success. Let's see some of the steps that will assist these firms in choosing the right CTMS.
Key Steps for Selecting Right Biotech Clinical Trial Management System
Prioritize Study Needs
Considering and prioritizing study needs is a crucial step in choosing the most reliable clinical trial management system for biotech companies. Prioritizing helps them to identify a solution that improves the study's quality and removes uncertainty for researchers when faced with difficult choices.
Hence, biotech and life-science organizations should choose a clinical trial system that is simple to use, well-organized, and suitably designed to minimize the number of clicks required to complete a task.
Select CTMS with Multiple Integrations
Integrated clinical trial management systems provide the best value for the companies’ funds as they guarantee the smooth functioning of research protocols. In addition, integrations are necessary to fully understand the importance and advantages of clinical trial management software for ensuring smooth transitions between site management and data collection.
Biotech and clinical research should look for CTMS platforms that can integrate with electronic medical record (EMR) platforms and clinical research process content (CRPC) billing grids. This will allow them to use the same billing designations and ensure compliance while minimizing the need for duplicate processes.
Ensure System Compliance and Security
Clinical research organizations need to adhere to a plethora of complex regulations in order to ensure compliance with one of the most challenging environments of principles, which is information security and privacy. Security and system compliance are vital aspects of choosing the right CTMS solutions for biotech firms as they assist in building trust and form a part of the system’s duties.
While selecting CTMS systems, it is essential for companies engaged in clinical research to ensure that these platforms are able to configure both, group and individual permissions, along with having a data backup and recovery plan for hosted systems. This will allow companies to assess the privacy and security implications of research and anticipate complications that may arise in each phase of the project.
Assess the Scalability
Choosing a scalable CTMS that can accommodate various types of fluctuations and expansions enables biotech and clinical firms to quickly adapt to fast-changing trends and demand spikes while reducing maintenance costs and enhancing user agility.
As scalability also means secure and expanded data storage, these businesses should instead use SaaS solutions than manually manage an ever-growing collection of hard drives. The right CTMS ensures accommodating the firm’s availability requirements without incurring the capital costs associated with expanding a physical infrastructure.
The Closing Thought
A well-executed and successful clinical trial involves multiple stages and processes. Several quality controls and stringent adherence to regulations are essential for the steps, along with efficient cross-departmental processes and procedures. Incorporating the right CTMS paves the way for paperless data collection, regulatory filing, and fiscal management tools for biotech researchers and administrative personnel.
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