VisionHealth's Kata^(R) Clinical to be included into Alcedis service platform for clinical studies

• Kata^(R) Clinical app supports clinical trials in the field of chronic lung diseases and can be customized to each trial's individual requirements
• Based on artificial intelligence (AI), Kata^(R) Clinical can improve both study outcomes and participants' experience

Munich (Germany), February 01, 2022 - VisionHealth GmbH, a pioneer in digital therapeutics (DTx) for the inhaled treatment of chronic lung diseases, today announced that Alcedis, a globally acting full service contract research organization (CRO) and market-leader for data driven clinical trial research and technology utilization, will implement the Kata^(R) Clinical into its service platform. Kata^(R) Clinical can be customized to meet the individual needs of each trial. It is designed to improve both study outcomes and participants' experience. Kata^(R) supports the correct inhalation of drugs using artificial intelligence (AI), thereby ensuring that the correct dosage is deposited in the lung.

"We are delighted to win Alcedis as a strong partner for data-driven clinical trials in respiratory diseases. The technology of Alcedis service platform brings together science, technology and innovation to offer customized concepts for highly qualitative studies," said Dr. Sabine Häußermann, CEO and founder of VisionHealth GmbH. "The incorrect administration of inhaled drugs is a common problem of chronic respiratory patients and effects both the outcome of therapy and clinical trials due to underdosing of the drug. Our Kata^(R) Clinical monitors the implementation of the therapy measures resulting in valid data. With such cooperations VisionHealth can improve the longitudinal patient outcome and contribute to better therapy results."

"We are always looking for innovative tools to facilitate the set-up, management and outcomes of clinical trials. With Kata^(R) Clinical, we have found an industry-leading approach for trials in the chronic respiratory field, which can really make a difference. Therefore, we are excited to work with VisionHealth and be able to include Kata^(R) Clinical into our service platform," Hanno Härtlein, Managing Director of Alcedis, commented. "The success of a clinical trial study in lung diseases is highly dependent on the patient adherence and the correct inhaler use. Kata^(R)'s innovative technology uses artificial intelligence to limit application errors. We are convinced that Kata^(R) Clinical will improve the study outcome by reducing the probability of false negative results."

Kata^(R) Clinical complies with the criteria of good clinical praxis (GCP) and meets all technical, regulatory and data protection regulations, qualifying it for the use in clinical studies. The Kata^(R) platform builds on VisionHealth's proprietary AI algorithm to monitor and support correct inhalator usage for the therapy of chronic lung diseases.

Chronic respiratory diseases like asthma and Chronic Obstructive Pulmonary Disease (COPD) are usually treated with inhaled drugs. The execution of the inhalation process is prone to errors: studies have shown error rates between 32 and 100 %.^{[1],[2],[3],[4],[5]} Not only therapy but also clinical study outcomes are highly dependent on properly applied drugs including inhaler usage and dosing. Incorrect inhalation results in underdosing of drugs, leading to data scattering and possibly invalid data. Kata^(R) Clinical trains the patient and controls the therapeutic inhalation, thus delivering trustworthy and consistent results. The Kata^(R) app controls the inhalation process and trains the patient by providing immediate feedback, thus delivering the support that is needed to regularly deposit the intended dose of the drug in the lung.

About VisionHealth
VisionHealth GmbH is a pioneer of digital therapy support for respiratory diseases. In cooperation with research institutions and selected industry partners, medical experts and IT experts, VisionHealth develops innovative and unique digital health solutions enabling sustainable improvements to existing standard therapies for patients with chronic lung diseases like asthma and COPD. The Munich-based private company was founded in 2017 by inhalation therapy specialists. Investors include business angels and private investors with many years of industry expertise, particularly in inhalation therapies.

About Kata^(R)
Kata^(R) is a VisionHealth proprietary platform based on artificial intelligence to support inhalation therapy. The aim of the Kata^(R) app for patients is to optimize the drug inhalation therapy of chronic lung diseases through digital support by help of augmented reality using the smartphone camera for immediate feedback and correction. Clinical evidence shows that patients frequently fail to correctly perform their necessary and regular inhalation due to a lack of therapy adherence or knowledge. As a result, the prescribed medications are not adequately delivered to the respiratory airways. A multitude of different devices for drug inhalation increases the training effort for physicians and patients and makes therapy monitoring almost impossible. This issue affects around 250 million people worldwide suffering from chronic lung diseases to whom Kata^(R) could bring urgently needed relief. Kata^(R) is a proprietary platform application providing a completely novel and unique combination of artificial intelligence (AI) and computer animation. Kata^(R) is among the first digital applications to have received medical device certification.

A modified Kata^(R) app for clinical trials (Kata^(R) Clinical) combines data and patient management to enhance the participants' experience and improve study outcomes at the same time. Based on the customized adaptation to the specific needs of a study, data collection and management can be conducted more efficiently and are less error-prone due to automation.

Kontakt
Dr. Sabine Haeussermann | CEO | 89 |
VisionHealth GmbH | Landsberger Str. 72 | 80339 München

Media Kontakt
MC Services AG
Katja Arnold / Dr. Brigitte Keller



^[1] Press VG et al. J Gen Intern Med. 2011; 26:635-42.
^[2] The Inhaler Error Steering Committee. Respir Med. 2013; 107:37-46.
^[3] Price DB et al. J Allergy Clin Immunol Pract. 2017; 5:1071-1081.e9.
^[4] Molimard M et al. Eur Resp J. 2017; 49:1601794;
^[5] Lindh A et al. Nursing Open 2019; 6:1519-1527;