How AI is managing the increasing complexity in medical technology
Product development in medical technology is becoming increasingly demanding and requires more specialists in development, regulatory affairs and quality management. Artificial intelligence (AI) can quickly search standards, summarise content, generate test cases and thereby support regulatory affairs and risk management. With AI, engineering teams can increase productivity by up to 40%, reducing labour costs or creating capacity for additional revenue.
Rising costs in development, quality assurance and approval
In today’s fast-paced world of medical technology, the ability to bring innovative products to market quickly is crucial to a company’s success. More sales through new products is the goal, and at the same time it is important to defend existing market niches. But despite the opportunities, the challenges should not be underestimated.
The development, quality assurance and market approval of medical devices are complex regulations that entail financial risks. Companies are faced with the challenge of correctly interpreting and implementing standards and regulations that are constantly updated and often difficult to understand in a strictly regulated market. In terms of areas, medtech companies are looking for specialists not only in sales and production, but especially in regulatory affairs and quality management. Experts from these areas, with medical technology expertise, are therefore not only expensive, but in some cases, especially with new regulations, simply not available. In addition, the scope and complexity of regulation has increased under the new regulations, which has further increased the pressure on some companies.
New opportunities using artificial intelligence
New developments in the field of artificial intelligence (AI) offer a great opportunity here. Imagine a tool that can automatically search through thousands of pages in seconds, understand contexts, break down complex content and, in doing so, refer directly to the relevant sections of standards and regulations provided. With AI, exactly such tools become reality (cf. example in Figure 1):
- Search thousands of pages in seconds: Instead of spending days or weeks searching for relevant information in thick manuals or online databases, an AI can provide precise answers in a fraction of a second.
- Breaking down complex content: The AI can not only find information, but also present and summarise it in an understandable form so that even non-experts can understand the requirements and specifications of standards – optionally in German or English.
- Referencing: Instead of providing general answers, an AI can refer directly to the relevant sections in the standards, so that users can be sure that the information provided is correct and up-to-date.
Figure 1: Example of a user interacting with an AI with hundreds of technical documents simultaneously.
Tools with intuitive and natural user interfaces make AI technology directly accessible even to non-IT experts. The application possibilities are manifold. Engineers and specialists from the area of risk management (cf. Figure 2) can be supported just as much as the areas of regulatory affairs, quality management, testing and product development. The basic prerequisite is always the provision of documents that ideally already exist in the company.
Figure 2: Exemplary results (excerpt) from the “Risk management for medical devices” application area
Let’s take a closer look at the risk management example. A company wants to develop a new medical device and needs to ensure that it complies with the current regulatory framework. Instead of consulting an expert or spending hours trawling through standards, the company can use AI to quickly build a comprehensive foundation. Within seconds, AI can not only identify the relevant standard (ISO 14971) from the company’s internal document base, but also prepare additional information from other relevant documents such as IEC/TR 80002-1 or assist in creating documentation itself, considering the required framework.
Overall, AI offers the potential to create solutions to the challenges companies face in regulatory affairs, product management and quality assurance. It enables companies to act faster, more efficiently and more safely and paves the way for innovation in the medical technology market.
Productivity gain through AI using the example of an engineering team with 5 employees
For decision-makers in engineering, this not only offers the qualitative advantages discussed so far, but also pays off financially. And this in two ways: On the one hand, the solution leads to an increase in productivity of 20 to 40%, which in turn leads to a significant reduction in personnel costs in a development project. This results from more efficient processes in analysis and technical texts, e.g. work with specifications and standards, and the generation of technical content, e.g. test descriptions.
If an engineering team with five members uses an AI solution, up to 1,760 working hours per year of development capacity can be freed up on the basis of empirical values and assumptions (see below). Evaluated at an internal cost rate of EUR 90 per working hour or an external hourly rate of EUR 150 per working hour, this results in a potential cost reduction of up to EUR 160,000 or an additional turnover potential of EUR 260,000 for the team per year. These values illustrate the enormous potential of AI to increase not only the quality of the work results, but also the productivity of an engineering team.
Figure 3: Unlocked working hours, reduced costs and turnover potential of an engineering team depending on the intensity of use and productivity gains.
The analysis is based on the following empirical values and assumptions:
- Number of users in the team: 5
- Working weeks per employee and year: 44 weeks
- Internal cost rate per hour: EUR 90
- External hourly rate: EUR 150
- Tool use per employee: 10 to 30 working hours per working week
- Productivity gain due to use: 20 to 40%
The bottom line? Artificial intelligence that pays off
In medical technology, the complexity of product development, quality assurance and market approval is constantly increasing. This leads to an increased need for experts in product development, regulatory affairs and quality management, who are often hard to find and expensive. Artificial intelligence can be used to search through thousands of pages of technical documents in seconds, summarise complex content in an understandable way and reference specific sections of standards directly, for example to create documentation or design tests. It can thus help teams interpret and implement standards and regulations efficiently, enabling them to act faster and more confidently. By increasing productivity by up to 40%, it can reduce personnel costs in development projects while creating capacity for additional revenue potential.
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This is achieved with a unique AI-driven toolchain that increases the productivity of product development teams from specification to testing with the lowest structural overhead.
Please note that all details and listings do not claim to be complete, are without guarantee and are for information purposes only.