Are Automation and AI the Future of Brain Scan Analysis?

After decades of development work, and trial and error and money spent, you might think that by the time your head is put inside a magnetic resonance imaging (MRI) scanner at a hospital, the difficult part of looking inside the brain is finished. But often it’s the analysis that comes after you leave the scanner that proves most challenging for physicians. The error rate for image analysis remains alarmingly high, and radiologists are being asked to handle and process larger numbers of scans every year. Can automation lend a hand? We talked to Dr. Chris Airriess, CEO at CorTechs Labs Inc., which has developed a post-processing scan software called NeuroQuant designed to streamline the analysis pipeline. We asked Chris about the current challenges in analysis, what datasets NeuroQuant would be trained on, and whether the general public will trust their medical scans to an AI.

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Biotech-365

Biotech 365 is an independent website, sharing information and news about Biotech and Biopharma : innovative Biotech companies, Biotech Jobs, Biotech tools, Bioinformatic softwares, Biopharma news, etc.

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MedTech

Biotech in 2022

Article | July 11, 2022

The robust global channel of more than, 800 gene and cell curatives presently in trials will produce clinical readouts in 2022, revealing what lies ahead for advanced curatives. The impact will be felt in 2022, no matter how you slice it. Eventually, how well industry and non-supervisory bodies unite to produce new frameworks for advanced therapies will shape the year 2022 and further. Pacific Northwest talent will continue to contribute to the advancement of gene and cell curatives in both the short and long term, thanks to its deep pool of ground-breaking scientific developers, entrepreneurial directorial leadership, largely skilled translational scientists, and endured bio manufacturing technicians. We may see continued on-life science fund withdrawal from biotech in 2021, but this can be anticipated as a strong comeback in 2022 by biotech industry, backed by deep-pocketed life science investors who are committed to this sector. A similar investment, combined with pharma's cash-heavy coffers, can result in increased junction and acquisition activity, which will be a challenge for some but an occasion for others. Over the last five years, investment interest in Seattle and the Pacific Northwest has grown exponentially, from Vancouver, British Columbia, to Oregon. The region's explosive portfolio of new biotech companies, innovated out of academic centres, demonstrates the region's growing recognition of scientific invention. This created a belief that continued, especially because Seattle's start-ups and biotech enterprises are delivering on their pledge of clinical and patient impact. Talent and staffing will continue to be difficult to find. It's a CEO's market, but many of these funds' return, and are not rising in proportion to the exorbitant prices they're paying to enter deals. This schism has become particularly pronounced in 2021. Hence, everyone in biotech is concerned about reclamation and retention.

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MedTech

Next-Gen Gene Therapy to Counter Complex Diseases

Article | September 22, 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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Medical

Next-Gen Genetics Cancer Therapies Creating Investment Prospects

Article | July 14, 2022

Genetic therapeutics such as genetic engineering and gene therapy are increasingly emerging as one of the most influential and transformed biotechnological solutions around the globe in recent times. These genetic solutions are being assessed across various medical domains, including cancer treatment, neurology, oncology, and ophthalmology. Citing the trend, the genetics industry is estimated to experience a tsunami of approvals, with over 1,000 cell and gene therapy clinical trials currently underway and over 900 companies worldwide focusing on these cutting-edge therapies. Growing Cancer Encourages Advancements in Genetic Technologies With the surging cases of cancers such as leukemias, carcinomas, lymphomas, and others, patients worldwide are increasing their spending on adopting novel therapeutic solutions for non-recurring treatment of the disease, such as gene therapy, genetic engineering, T-cell therapy, and gene editing. As per a study by the Fight Cancer Organization, spending on the treatment of cancer increased to $200.7 billion, and the amount is anticipated to exceed $245 billion by the end of 2030. Growing revenue prospects are encouraging biotechnology and biopharmaceutical companies to develop novel genetic solutions for cancer treatment. For instance, Bristol-Myers Squibb K.K., a Japanese pharmaceutical company, introduced a B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T cell immunotherapy, Abecma, for the treatment of relapsed or refractory (R/R) multiple myeloma in 2022. Amid a New Market: Genetics Will Attract Massive Investments Despite several developments and technological advancements, genetics is still considered to be in a nascent stage, providing significant prospects for growth to the companies that are already operating in the domain. Genetics solutions such as gene therapies, gene editing, and T-cell immunotherapy are emerging as highly active treatments across various medical fields, resulting in increasing research and development activities across the domain, drawing significant attention from investors. Given the potential of genetic treatments and the focus on finding new ways to treat cancer and other related diseases, it's easy to understand why companies are investing in the domain. For instance, Pfizer has recently announced an investment of around $800 million to construct development facilities supporting gene therapy manufacturing from initial preclinical research through final commercial-scale production. Due to these advancements, cell and gene therapies are forecast to grow from $4 billion annually to more than $45 billion, exhibiting growth at a 63% CAGR. The Future of Genetics Though there is a significant rise in advancement in genetic technologies and developments, the number of approved genetic treatments remains extremely small. However, with gene transfer and CRISPR solutions emerging as new modalities for cancer treatment, the start-up companies will attract a growing amount and proportion of private and public investments. This is expected present a tremendous opportunity for biopharma and biotechnology investors to help fund and benefit from the medical industry's shift from traditional treatments to cutting-edge genetic therapeutics in the coming years.

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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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Biotech-365

Biotech 365 is an independent website, sharing information and news about Biotech and Biopharma : innovative Biotech companies, Biotech Jobs, Biotech tools, Bioinformatic softwares, Biopharma news, etc.

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.

Read More

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