Digital Chameleon & Prof. Dr. Oliver Haase pair up
Machine learning. We all heard about this fairly new technology based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention, yet it probably remains still quite abstract to many people so far. That said machine learning is already firmly anchored in our daily routines for years without us actively noticing. Self-driving cars, speech recognition tools or effective web research are all the fruit of machine learning within the last decade. Thus, it is fair to say that machine learning is certainly amongst the most promising future trends within the artificial intelligence movement but that it already has pervasively found its place in our modern life of today. Over the past years machine learning has increasingly become a powerful tool to leverage business-decision making processes to the next level. A potential that has not remained unnoticed as a recent study from IDG reveals that almost two thirds of interviewed companies already use machine learning applications or are in the process of implementing those. These represents a 20% increase compared to the previous year. The study also shows that the advocates for machine learning are prevalently found in the C level ranks.
It is undeniable that machine learning represents a massive business opportunity to optimize processes, decrease costs, cater new business models and create innovative products. On the more “challenging” side though this technology requires a high level of expertise and poses new risks if not appropriately governed.
In the medical device sector the software development process is regulated by IEC standard 62304. This standard, however, does not fit well the data-centric development process for machine learning applications. We are currently in a transition phase in which standards and regulations for machine learning based products are still in the making. Manufacturers align and consolidate their good practices, proposed SOPs and development processes aiming to fill the regulatory gap while regulatory authorities are sorting out the establishment of the regulatory framework for machine learning application.
A challenge that is very familiar to Prof. Dr. Oliver Haase, professor at the Konstanz University for Applied Sciences and consultant in the field of machine learning for medical devices. His scope is helping medical device manufacturers to bring machine learning based medical devices into the market in a fast, safe, and painless manner. Being an expert in the field of machine learning he knows the ins and outs and helps manufacturers to establish state of the art processes for a successful machine learning development and validation. In his opinion the trend of regulatory requirements becoming more demanding will pertain in the future, especially in the relatively new field of machine learning. Therefore, for medical device manufacturers, a structured and thorough development and validation strategy will be key to success. A statement that Digital Chameleon shares and perfectly aligns with our own vision regarding Digital Transformation.
These common points of views became apparent very quickly when Prof. Dr. Oliver Haase and Tanja Rohark (CEO & founder of Digital Chameleon) first met at the Johner Institute (Konstanz). During further conversations the idea developed that Prof. Dr. Haase and its Validate ML team would be a perfect partner to complement our Digital Transformation product and extend our services into the field of machine learning. In our process to set in place an integrated management system that synchronize business & technical processes by marrying QMS with Information Security, the services provided by Validate ML would come into play when drafting the ideal QMS landscape for our customer.
This service comes in various “shapes and sizes” depending on the individual project and client needs. It ranges from mentoring services, via providing a framework and SOPs for a relgulatory compliant machine learning development process, coaching along all phases of a typical machine learning pipeline and library validation, up to the accompaniment of machine learning products market approvals by providing guidance to achieve audit readiness.
“I have a tremendous respect and admiration for Prof. Dr. Haase´s work and knowledge and see him as an extremely valuable asset in our partner network. The collaboration with him offers an inspiring exchange and galvanizes the urge to explore new territories, become creative and innovative and to refine our Digital Transformation customer journey. I am truly grateful to be surrounded by a partner network that holds highly skilled experts of their field and to bring our vision to live: Creating a Digital Transformation product from one single source that covers all implicated areas on a high-quality level.”, - says Tanja Rohark.
“Establishing a regulatory compliant process for machine learning development is a key ingredient in the digital transformation of medical device manufacturers. Digital Chameleon is the perfect partner for this endeavor. Not only because of their profound expertise and holistic approach to digital transformation, but also for their business philosophy that puts the human component first." - adds Prof. Dr Haase.
With respect to this collaboration one thing is for sure: Two enthusiastic and passionate parties met one another striving for innovative and future driven digitalization approaches.
Digital Chameleon is very proud and thrilled to closely collaborate with Prof. Dr. Haase and team and cannot wait to put our ideas and vision into practice.
Sources: 1 IDG Studie Machine Learning 2020