CNC Intelligence Review, Artificial intelligence can assist companies discover new opportunities as well as products to keep ahead of competitors. Senior managers in software should be aware of the fundamentals of how this technology works, the reason that agility is essential in the development of AI solutions. As well as the best way to recruit or train employees for new roles, says CNC Intelligence Review.
AI or ML
Alliata stated the fact that AI or ML are being increasingly used in various industries such as movies to self-driving vehicles and are likely to be a significant influence on business in the coming years.
Software developers must be able to comprehend the way in which the creation of ML models differs from normal software development. To handle this ML development process properly it is crucial to be agile through a method that allows rapid pivots, iterations, and continual improvements, Alliata said.
According to Alliata, software managers must be ready to recruit or train for roles such as data scientist engineers in data, ML engineering. The role may not exist yet in the current engineering teams for software and require specific capabilities.
InfoQ interviewed Zorina Alliata on the topic of implementing AI and ML at work.
Artificial Intelligence (AI) and Machine Learning (ML) can be described as a field of computing science, statistics and engineering that employs models or algorithms to complete tasks and demonstrate behavior such as learning taking decisions, making judgments as well as making forecasts. ML is thought to be an aspect of AI which allows models to be created by training algorithms through the analysis of data, but without models being specifically programmed.
What role can AI/ML play in the process of developing drugs?
FDA acknowledges the growing use of AI/ML across the development process and across many therapeutic areas. In actuality, FDA has seen a substantial increase in the number of applications that incorporate AI/ML-related components in the last several years. In fact, there will be over 100 submissions being reported by 2021. The submissions cover the whole spectrum of drug development ranging from the discovery of drugs and clinical research to post-market safety surveillance and advanced manufacturing of pharmaceuticals.
In addition, AI/ML is becoming integrated into areas in which FDA is actively involved in, such as Digital Health Technologies (DHTs), and Real-World Data (RWD) analytics.
What is FDA's view regarding using AI/ML for the development of drugs?
FDA is dedicated to ensuring that medicines can be used safely and effectively, while helping to facilitate innovation in their creation. Like all innovations, AI/ML creates opportunities and new issues. To tackle these challenges, FDA has accelerated its efforts to establish a more agile regulatory system that will allow innovation while protecting the public health.
In the course of this initiative the FDA's Center for Drug Evaluation and Research (CDER) is, working in partnership together with Center for Biologics Evaluation and Research (CBER) and the Center for Devices and Radiological Health (CDRH) published an initial paper of discussion to engage with a variety of stakeholders and explore pertinent considerations regarding AI/ML's use in the creation of biological and pharmaceutical products. FDA will continue to seek feedback to improve research in this field.
AI/ML is certain to play a significant part in the development of drugs, and FDA is planning to develop and implement a flexible regulatory framework that is based on risk, which encourages innovation while ensuring safety for patients.
