Machine Learning in Biology: Top ML Use Cases Advancing Biotech Industry

1. Machine Learning in Biology: Top ML Use Cases Advancing Biotech Industry September 2, 2021 Dash Technologies Inc Machine Learning The advent of digitalization has made 21st-century data-centric, sparing no industry or sector from its effect. Healthcare, biology, or biotech sectors are no immune to the impact. Enterprises are working towards finding the possible solution to integrate their businesses with the powerful resolution and bestow the ability to capture, share and deliver data systematically, faster and smoother.

2. The subdisciplines of biology, such as bioinformatics, computational biology, system biology, and others, have long been struggling with biological data processing issues. The trending technologies, like Artificial Intelligence, Machine Learning, data analysis methods, predictive models, computer science algorithms, and Big Data, help those sectors find the right solution and tackle the challenges posed by data. The technology is already helping the Biotech industry and solving all their data- related issues. Simply put, the recent and ongoing health crisis —COVID-19 is the most significant example. AI and ML are unequivocally rising and they have their equal participation in the fight against deadly coronavirus. But, this is not the only example or use case of Machine learning in biology. There are plenty of them, and you would love to know about them. So, here we go; 1. Machine Learning in Medical Diagnostic Devices As the use of the smartphone is growing incessantly, they are comping equipped with more power and ability to support hardware-accelerated neural network training and inference. And that allows Machine Learning software like TensorFlow and Core ML to efficiently run Neural networks on intelligent devices, enabling them as innovative medical diagnostics. Let’s take an example of a smart portable ultrasound device: The solutions enable healthcare to allow consumers to view ultrasound imagery in real-time by connecting the Machine Learning software to consumers’ devices. Consumers, through real-time imagery, can monitor their womb, heart, lungs, and other organs. Whether you are a biotech scientist, running health care, or own a hospital, having this innovative device delivers fast, accurate, and smart treatment to users by offering them faster, convenient, and cost-effective treatment.

3. 2. Machine Learning Apps to Fight Against Coronavirus No doubt, we have lost millions of invaluable lives in the fight against COVID-19 worldwide, but millions of other lives have been saved by scientists by discovering and creating vaccines and other drugs in record time. You must be thinking where Machine Learning lies in the entire process? The team of scientists and doctors needed technological support to developing vaccines to find the part of the virus that was most likely to stimulate an immune response. This process would have taken a year or two to reach a conclusion, while Machine Learning powered software helped the team find the solution quickly. And, the result is before us. You must have heard about popular Machine Learning models named NetMHCpan and MARIA. These models were based on neural networks, supporting the team to accurately anticipate receptor and protein interactions and cancer immunity responses, respectively. 3. Machine Learning Actively Supports Healthcare in Cancer Treatment Cancer is a deadly disease, and after a certain level, it is impossible to treat. Thousands of lives are lost through years of cancer. The challenge for doctors is to catch the disease at its early stage. Besides, cancer involves various treatment approaches, including chemotherapy, immunotherapy, and others.

4. The treatment approach widely differs from one person to another and the type of cancer to another. That means a treatment approach that worked well for one person may not work for another. Or, the approach that worked for one type of cancer may not work for another. That complex treatment approach is known as variability. That’s where Machine Learning Software Solution jumps in, helping doctors and biotech scientists design personalized cancer treatment. It involves various processes, and the outcomes depend on the quality of software based on ideas built. 4. ML Software Helps in Drug Discovery Drug discovery traditionally involves highly complex procedures involving high resource, time, and intensive trial and error requirements. A single step in drug discovery requires hundreds of manual processes and days or every month of time. Machine Learning, along with its subsets like deep learning and neural networks, can automate, accelerate and scale the process and help biotech scientists or medical specialists discover drugs systematically faster. Usually, the drug discovery process involves; •Discovery and Development

5. •Preclinical Research •Clinical Research •FDA Review All these processes are interdependent. The process passes, the second process will be initiated. The cycle continues till the drug finally reaches the medical stores or healthcare facilities. These processes seem easy, but they take years of time to get to the final stage. And, if it is for a complex disease, like COVID-19, then it takes even two years to discover the right drug and get it finally approved by the government healthcare department. In all these processes, as we have witnessed in the case of a novel coronavirus, how quickly our biotech scientists and healthcare experts came up with the solutions and saved millions of lives, Machine Learning can make thighs easier. 5. Machine Learning in Mental Illness Prediction, Diagnosis, & Treatment Did you know around 10% of the global population is suffering from mental disorders, which cause around $10 trillion of economic loss yearly? Anxiety, depression, substance use disorder, eating disorder, etc., are the parts of mental illness. The bad part is that most people go untreated as they never know if they are going through any disorder. That’s shocking but a cruel fact. Even doctors and scientists were not so successful in predicting mental disorders until now. Yes, technological advancement has enabled healthcare experts to build smart solutions that not just indicate mental illness but also suggest the correct diagnosis and treatment method.

6. Do You Have An Innovative Device Idea? Machine Learning has immense capabilities, helping all industries streamline their business process and get profits. Biology is no different. It has plenty of things to offer. Machine Learning can help you build; •Smart Wearable •Intelligent Administrative Process •Smart Software to help you in healthcare research •Predict disease at an early stage •Find the correct diagnosis and treatment •Smart Chatbots •Enable mobile health •And many others. In short, a problem that traditionally was complex or difficult or impossible is easy and possible —thanks to the continuous advent of machine learning. You can have the right ML software or your biotech facilities or healthcare, though the right Machine Learning expert will help you get even better solutions at affordable costs. Final Thoughts We have explained how Machine Learning is changing the modern biotech industry by helping biotech scientists and healthcare professionals get the right solution. Machine learning is the present and the future, especially for biotech sectors that also include clinical research facilities, hospitals, the pharmaceutical industry, and others. Get it now and stay competitive, stay streamlined. Remember: the future is coming. We hope you understood Machine Learning in biology. In case, need any requirements, suggestions, or want to build Machine Learning Software Solutions, we are here to help. Let’s connect.