How smart assistants can be used in the life sciences industry
Manfred Hörter, senior manager and Lena Löhe, consultant at msg advisors, explain how smart assistants can be used for industrial use in life sciences.
Artificial Intelligence (AI) and Augmented Reality (AR) are key technology trends that are conquering and changing industrial sectors in an evolutionary and disruptive manner. Both in health care as well as within the pharmaceutical and medtech sectors, this opens up opportunities to rethink operational processes. The application options are numerous and range from the pharmaceutical and medical device industry to the diagnosis of diseases, patient care and the support of doctors and nursing staff.
Perhaps its most valuable benefit is the ergonomic and intuitive automation of routine processes. This results in more time-efficiency, reduces the error rate and allows for greater focus on the process steps that require human intelligence. This can be the case, for example, when individual problems need to be solved creatively, in form of employee guidance systems or other potentials for improvement that need to be leveraged. By using AR and data glasses, computer-aided visual information can be displayed while working - which is equally helpful in quality departments, in the laboratory, on the production line or during patient appointments.
AI-based software tools also offer support in the execution of standardisable tasks in life science and healthcare. But how do you gain an overview considering the abundance of technological innovations? How can AI and AR specifically improve efficiency, quality, agility and compliance in an organisation's central operations? Here are three application examples that we have realised for our customers with this objective in mind.
msg.COVID-19-Bot: Information transfer via AI and chatbot
During the corona pandemic, the information situation has and continues to develop at an extremely rapid rate, for example with regard to the disease pattern, preventive measures, general conditions as well as government regulations. Call and service centres are often overloaded by the high volume of enquiries and the rapidly changing information situation. In addition, missing or incorrect information can have significant consequences (infection or illness, production and sales losses, etc.). It is therefore important to ensure that any inquiries are answered promptly and correctly - i.e. based on the information compiled in pandemic plans and from other reliable sources of information.
This is where the msg.COVID-19-Bot from msg systems ag provides valuable assistance. In its capacity as a digital assistant, it provides support to call/service centres on all questions surrounding COVID-19. The AI-based chatbot is continuously updated with relevant data from official sources such as the German Federal Ministry of Health or Johns Hopkins University, but can also integrate individual and local information, directives or pandemic plans. A free open version of the msg. COVID-19 bot is available for integration into any website.
We can also apply these AI-based principles to the requirements of the life science industry by reconfiguring the bot to be an interactive GxP lexicon. The applicable legal regulations and official requirements are then used as the data source. Customisation according to individual specifications is also possible.
AI in quality control
Quality control is one of the main fields of application for artificial intelligence in the industrial sector. We have developed use cases for automation and the improvement of quality control in pharmaceutical production based on AI applications from the manufacturing control area of highly automated industries such as the automotive industry. As an example, camera systems and imaging techniques in combination with machine learning can support the QA process in detecting quality defects. Machine learning systems play a central role in complex inspection tasks, as they are able to flexibly and quickly detect a large variety of products and a wide range of defects and flaws.
One application example is a camera system that, in conjunction with automated image recognition, can be used to monitor pill production or the filling of vials and report quality deviations such as damaged products, which are then automatically eliminated. This not only automates the monotonous process of quality control, but also automatically categorises any defect products and documents them in the system. The advantages are not only a reduction in manual effort for individual plant workers, but also lower production costs and faster, more transparent availability of documented information.
AI-supported augmented reality and language assistants
Augmented Reality (AR) refers to technologies that enhance real-time visual information with additional data such as text, graphics, images, animations or videos on data glasses in real-time. An application example: a pharmaceutical and medical technology company has to regularly change over its production machines due to the high product diversity and has to make numerous adjustments in the process. Retooling is therefore a monotonous, time-consuming and error-prone process that requires a high level of concentration on the part of the operating personnel. By using data glasses and AR, the individual steps are now displayed to the operator directly at the machine. This eliminates the need to study work instructions or teach-in procedures. The set-up time is reduced drastically, while error rates drop considerably.
AI-supported voice assistants provide the same effect, supporting service staff or technicians by answering their questions via headset in an interactive dialogue, facilitating work for the employee. Consider, for example, when the question of how to correctly attach or wire a certain component during the assembly of a complex medical device occurs. Previously, the technician had to check their written documentation, whereas now the voice assistant immediately provides him with the information he needs. As a result, the technician is not interrupted in their current work process, their attention remains focussed and the workflow is improved.
These three use cases provide a first impression of the digitalisation potential offered by AI and AR technologies in the pharmaceutical and medical technology sectors. It goes without saying, that, when using AI, there will always be the question of how it can be used appropriately without losing sight of regulatory and ethical requirements. After all, quality managers in life science companies must not necessarily focus on technological developments, but rather fulfil their duties.