KIELTYKA GLADKOWSKI KG LEGAL takes part in the project “Systemic Design and Sustainable Healthcare for MedTech Manufacturing (SysteMA)”. One of elements of the project is led by the Life Science Cluster in Krakow and the MedSilesia cluster. The latter became involved in activities to raise awareness and knowledge in the field of the circular economy.
The research is part of the EIT Manufacturing project SysteMA (Systemic Design and Sustainable Healthcare for MedTech Manufacturing), which focuses on the role of MedTech manufacturing towards the environmental, social, and economic sustainability of healthcare systems. The project aims to create online training courses on this topic, providing EU companies with actionable skills to improve the sustainability of their products and processes and seize new market opportunities.
Real World Data (RWD) is data collected in the real world about patient health and healthcare delivery. This data can be collected routinely from a variety of sources including electronic health records, disease registries or patient generated and uploaded data. RWD allows for the collection of more data from actual users of medicinal substances. Real World Evidence (RWE) is clinical evidence that has been carried out on the basis of RWD analysis. They concern the benefits or risks of using a medicinal product. RWE is obtained from various studies and analyses such as randomised trials, including large simple trials, pragmatic trials or observational studies. They can be used to determine what action should be taken to reduce the risks and increase the benefits of a medicine for therapeutic purposes. RWE has been defined in Sec. 3022 (2) of the 21st Century Cures Act: ‘real world evidence’ means data regarding the usage, or the potential benefits or risks, of a drug derived from sources other than randomized clinical trials. Clinical trials are now at the heart of the process of bringing medicinal products and medical devices into use. For the most part, they are conducted even before a product is placed on the market, but the final, fourth phase takes place after the product is marketed. This phase consists of determining whether the marketed product is safe in all manufacturer’s indications and for all patient groups. Conclusions from previous phases are further verified in this phase. In the earlier phases, studies are conducted on a group of volunteers on whom the effects of the substance are tested. In the final phase, information is collected on adverse drug effects that have been reported. In this aspect, RWE and clinical trials are similar. However, there is one important difference that weighs in favour of RWE. In the case of clinical trials, data are collected only from patients who have reported adverse effects and the information about them has reached the manufacturer. RWD can be collected from all patients who reported an adverse reaction to a medicine and the adverse reaction was reported in their medical records. The number of people from whom data on the effects of medicines are derived is therefore much larger than in the case of clinical trials. Manufacturers of medicinal products and medical devices use RWD and RWE to support clinical trials, especially their final phase. They are therefore not mutually exclusive modes of research, but rather designed to support each other.
Due to the registration qualifications, there are innovative and generic drugs as well as preparations with the so-called well established use. Companies producing innovative (original) drugs are of great importance in the development of new technologies. However, the pharmaceutical industry in Central and Eastern Europe is dominated by companies producing generic drugs (the so-called generics). Generic drugs are equivalents of original products, the patent protection of which has already expired or has not been applied for. The original and generic medicine may differ in name, manufacturer and price. However, the active substance contained in them, which is responsible for the action of the drug, and its amount will always be the same. Analysts say that the generic drugs market in 2008 was worth EUR 17.2 billion, and predict its further development. Also in Poland, generic companies have a large share in the pharmaceutical sector. Among many European countries, it is Poland that is the leader in terms of value and quantity of generic drugs sold. In terms of value, generic drugs constitute 88% of the drug market in our country, and in quantitative terms – approx. 66%, which is definitely more than in other countries.
An important part of the tasks of the Polish Agency for Health Technology Assessment and Tarification is the evaluation of medicines. The recommendations/positions and opinions issued mostly concern medicinal products. Pharmaceutical technologies are evaluated at the Agency at the request of the Polish Minister of Health.
In the Polish health system, citizens’ access to medical technologies (pharmaceuticals, medical devices, medical procedures and organizational systems) is regulated by the insurer – the National Health Fund – based on a technology assessment. Health Technology Assessment is of increasing importance in medical technology reimbursement decision-making, providing a rational basis for these decisions.
The Guidelines for the Evaluation of Medicinal Products (Version 3.0) indicate how the evaluation of pharmaceuticals should take place:
Artificial intelligence (AI) used in medical devices
Artificial intelligence (AI) technologies are being used more and more boldly in areas that until now were reserved exclusively for humans. They are mainly used in decision-making, image analysis, speech, or natural languages analysis. These systems involve creating models of intelligent behaviour that can be used in computer programs and solve problems that cannot be solved using standard classical algorithms. This requires large amounts of data through which AI applications learn patterns and features that predict the output. This makes them different from classical algorithms, which have predefined rules and which AI creates on its own based on data provided to it. In medical devices AI causes operational speeding up of mechanisms and analysis of particular cases.
Artificial intelligence in medical diagnosis and prognosis