MedTech
Article | July 12, 2022
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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Medical
Article | July 14, 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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MedTech
Article | September 22, 2022
Natural remedies have been employed in medicine since antiquity. However, a large number of them fail to go past the clinical trial stages. In vivo instability, poor solubility and bioavailability, a lack of target-specific delivery, poor absorption, and side effects of the medication are only a few of the problems caused by the use of large-sized materials in drug administration.
Therefore, adopting novel drug delivery systems with targeted medications may be a solution to address these pressing problems. Nanotechnology has received tremendous attention in recent years and has been demonstrated to help blur the boundaries between the biological and physical sciences. With great success, it plays a vital part in enhanced medication formulations, targeted venues, and controlled drug release and delivery.
Limitations of Traditional Delivery Trigger the Adoption of Nanoparticles
The field of nanotechnology and the creation of drug formulations based on nanoparticles is one that is expanding and showcasing great potential. It has been thoroughly researched in an effort to develop new methods of diagnosis and treatment and to overcome the limitations of several diseases' current therapies. As a result, nanoparticles are being used to improve the therapeutic effectiveness and boost patient adherence to treatment by increasing medication bioavailability, drug accumulation at a particular spot, and reducing drug adverse effects.
The nanoparticles could be transformed into intelligent systems housing therapeutic and imaging agents by manipulating their surface properties, size, correct drug load, and release with targeted drug delivery.
Nanostructures facilitate the release of combination medications at the prescribed dose since they remain in the blood circulation system for a long time. Therefore, they result in fewer plasma fluctuations with decreased side effects. Due to their nanoscale, these structures can easily enter the tissue system, promote the absorption of drugs by cells, make medication administration more effective, and ensure that the medicine acts at the targeted location.
The Way Ahead
Nanomedicine and nano-delivery systems are a comparatively new but fast-evolving science in which nanoscale materials are used as diagnostic tools to deliver drug molecules at precisely targeted sites in a controlled manner. It is finding applications for the treatment of diseases such as cardiovascular, neurodegenerative, cancer, ocular, AIDS, and diabetes, among others. With more research and technological advancement, these drug delivery solutions will open up huge opportunities for companies that work with them.
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Industrial Impact
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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