Blood-based biomakers to monitor stromal conditioning in cancer

| February 25, 2019

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The concept of liquid biopsy has generated much scientific and commercial enthusiasm as it starts with a very accessible sample type - a body fluid, typically blood, rather than a surgically extracted tissue.

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Spero Therapeutics

Spero Therapeutics is a global multi-asset clinical-stage biopharmaceutical company headquartered in Cambridge, Massachusetts dedicated to developing a novel and highly differentiated pipeline of antibacterials focused on unmet needs of patients with drug resistant bacterial infections.

OTHER ARTICLES

Biotech: Finding The DNA For Success

Article | April 3, 2020

The integration of artificial intelligence within life sciences is making drug discovery and development more innovative, less labor intensive and more cost-effective, says Deloitte’s annual global outlook. According to Deloitte’s 2020 Global Life Sciences Outlook, the biotech sector is at an inflection point. To prepare for the future and remain relevant in the ever-evolving business landscape, biopharma and medtech organizations will be looking for new ways to create value and new metrics to make sense of today’s wealth of data, the report overview says. As data-driven technologies provide biopharma and medtech organizations with treasure troves of information, and automation takes over some mundane tasks, new talent models are emerging based on purpose and meaning. The integration of artificial intelligence (AI) and machine learning approaches within life sciences is making drug discovery and development more innovative, time-effective and cost-effective, the Deloitte report states.

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INDUSTRIAL IMPACT

AI and Biotechnology: The Future of Healthcare Industry

Article | April 3, 2020

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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MEDICAL

Better Purification and Recovery in Bioprocessing

Article | April 3, 2020

In the downstream portion of any bioprocess, one must pick through the dross before one can seize the gold the biotherapeutic that the bioprocess was always meant to generate. Unfortunately, the dross is both voluminous and various. And the biotherapeutic gold, unlike real gold, is corruptible. That is, it can suffer structural damage and activity loss. When discarding the dross and collecting the gold, bioprocessors must be efficient and gentle. They must, to the extent possible, eliminate contaminants and organic debris while ensuring that biotherapeutics avoid aggregation-inducing stresses and retain their integrity during purification and recovery. Anything less compromises purity and reduces yield. To purify and recover biotherapeutics efficiently and gently, bioprocessors must avail themselves of the most appropriate tools and techniques. Here, we talk with several experts about which tools and techniques can help bioprocessors overcome persistent challenges. Some of these experts also touch on new approaches that can help bioprocessors address emerging challenges.

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Ruminating on Bioprocessing 4.0

Article | April 3, 2020

The Bioprocessing 4.0 concept seeks to apply automation and technology to the digital transformation of biologics manufacturing. As the paradigm moves forward, it faces barriers to its adoption, according to Eric Langer, president of BioPlan Associates. “Perhaps the greatest challenges involve unsecured links and adapting the applications to areas where automation is critically needed today,” says Langer. “Unresolved security issues could seriously affect a company’s data in a regulated environment, so they will need to have iron-clad anti-hacking protection in place. Unfortunately, cyber security is not yet a top focus for the industry.”

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Spero Therapeutics

Spero Therapeutics is a global multi-asset clinical-stage biopharmaceutical company headquartered in Cambridge, Massachusetts dedicated to developing a novel and highly differentiated pipeline of antibacterials focused on unmet needs of patients with drug resistant bacterial infections.

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