Undoubtably, AI was the keyword that dominated technology and new product reviews across all industries for 2023. This comes as no surprise, as AI was offered to the masses like never before – mainly through ChatGPT.

AI has been characterized over the past many decades from several periods of high activity and outputs, followed by “AI winters.” Today we obviously experience a high activity period with lots of outputs and 2023 has been very AI intense, because everyone with Internet access was able to validate its capabilities.

Life Sciences is among the industries with the highest impact of AI, but at the same time one of the most regulated ones. Large Language Models (LLMs) like GPT-4, LLaMA and Gemini are already used for various health and clinical applications like drug discovery, clinical protocol design, documentation, image analysis, task automation, virtual assistant and many more and the expectation is that these will grow much in the coming years. At the same time, regulators around the world are working hard to create the appropriate framework to control AI, in a way to promote transparency, prevent discrimination, protect privacy, enforce safety, and foster responsible innovation. Recently, the AI Task Force of the eClinical Forum and the European CRO Federation (EUCROF), published a white paper presenting the state of play and providing information about AI and ML in clinical research around the globe, with emphasis in US and Europe. Sofoklis Kyriazakos, leader of the AI joint Task Force, says “This white paper is an important milestone for the industry that sees the benefits of AI and puts efforts to understand the environment and how to transform the challenges into opportunities. This has been a very nice team work that underlines the importance of joining forces to make a step forward and adopt AI technologies.”

The year 2024 will start with the stakeholders of the industry being widely exposed to the capabilities of generative AI, most of them having invested resources to investigate or even to deploy such solutions and being more realistic on other matters with emphasis on the feasibility and compliance. We expect that 2024 will be the year of design, development, and compliance for the industry to create solid grounds for the adoption of AI. In Innovation Sprint we perform high impact research and development to identify AI features that can add value to Healthentia and follow a thorough process for implementation to become commercially available in minimum time.

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Study Description

ONCODIR (Evidence-based Participatory Decision Making for Cancer Prevention through implementation) will identify risk factors associated with colorectal cancer (CRC) and will integrate multidisciplinary research methods and technologies (including health policy analytics, artificial intelligence, and decision support theories) to deliver evidence-based and personalized recommendations on colorectal cancer prevention.

Study Details

• Type: HORIZON-RIA, HORIZON-MISS-2022-CANCER-01-01
• Start: 1/6/2023
• End: 1/11/2026
• Duration: 42 months

Our Role

Innovation Sprint will be offering Healthentia for use by healthy citizens to collect data for CRC prevention. Healthentia will be offering advice on citizens’ behavior, based on the collected data and the resulting citizen understanding.

To that extend, Healthentia will be extended both in terms of functionality and content. The new functionality involves:

(1) the development of a new biomarker widget to display risk prediction results automatically collected from other modules of ONCODIR.

(2) the creation of a Kafka client, producing towards, and consuming from ONCODIR, to facilitate integration with the rest of the project.

(3) the introduction of a mechanism to wrap recommendation messages into a dialogue, facilitating both delivery and feedback towards clinicians and policy makers.

In terms of content, CRC-related questionnaires will be facilitated, and a dialogue for recommendation wrapping will be created. The resulting solution will be tested in terms of technology readiness in Laboratory Integration Test 2 and will be delivered to the large-scale pilots for use by the citizens.

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Study Description

HumAIne facilitates advanced and reliable collaboration of experts and AI towards hybrid decision making and support in a variety of industries. It delivers the HumAIne Operating System, built on four technological pillars: Active Learning (AL), Neuro-Symbolic Learning, Swarm Learning (SL), and eXplainable AI (XAI). The HumAine OS enables AI solution creators to build advanced Human-AI collaboration systems that outperform standalone AI and individual experts’ efforts.

Study Details

• Type: HORIZON-RIA, HORIZON-CL4-2022-HUMAN-02-01
• Start: 1/10/2023
• End: 1/9/2026
• Duration: 36 months

Our Role

Innovation Sprint leads the project’s efforts on defining the vision and specifications for human-AI collaboration, focusing on user requirements extraction and use case scenarios definition. These efforts lead on the needs to be covered by the technology developed in HumAIne. We also lead the healthcare pilot, where the HumAIne technology will be leveraged to enhance the AI modules in the patient understanding and advice delivery systems of Healthentia.

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The “AI state-of-play around clinical research” is a white paper recently published by the AI joint Task Force from the European CRO Federation (EUCROF) and the eClinical Forum (eCF). This is a position paper that provides information about AI and ML in clinical research around the globe, with emphasis in US and Europe.

The use cases presented include: AI to enhance clinical trial operations, feasibility exploration according to inclusion/exclusion criteria for recruitment, patient and site recruitment, applications to improve trial operations, risk-based monitoring and data management, task automation, applications for Real World Evidence (RWE), medical coding, and more.

The paper also presents clinical evaluation challenges for the development and validation of AI and concludes with the positions of the AI Task Force, including the promise for improving treatments and clinical research, the risks, and the challenge for using AI given the current state of evolving regulations.

Sofoklis Kyriazakos, leader of the AI joint Task Force, says “This white paper is an important milestone for the industry that sees the benefits of AI and puts efforts to understand the environment and how to transform the challenges into opportunities. This has been a very nice team work that underlines the importance of joining forces to make a step forward and adopt AI technologies”.

See publication: https://www.eucrof.eu/images/23_11_06_AI_State-of-Play_Around_Clinical_Research_15Sep23__vPR1_Approved_by_eCF_SC_for_Release.pdf

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A digital therapy pathway is a healthcare method that employs technology to provide support and therapy services to patients remotely.  These technologies can include wearables and a mobile app for collecting data, an online platform for visualization purposes, video conferencing and chatting for direct communication between clinicians and patients, and a virtual companion service that can support the patient by giving personalized advice [2].

Typically, the process of digital therapy includes many steps [3]. These can include:

1. A first assessment of each patient to determine the best therapy approach
2. Set of clear goals that are specific, measurable, and achievable defined by healthcare professionals
3. Progress monitoring with the use of questionnaires and other digital tools allows healthcare professionals to keep track of the effectiveness of the treatment and adjust it as required

For the last step, a digital evaluation method of the data collected can be implemented where the predefined goals are transformed into critical rules for the health progression. This performance assessment can automatically alert the patient through the mobile app when a measurable attribute is out of range or provide guidance, feedback, and support as patients work towards achieving their goals. This will be achieved with the use of a virtual companion service, that will trigger a dialogue on a regular basis in order to give advice in a personalized manner to ensure progress towards the goals.

To conclude, digital therapy pathways can be an effective way to deliver therapy services to patients who need continuous monitoring and have difficulty accessing traditional in-person therapy, such as those who have mobility issues and also it can thrive in areas where demand for traditional treatment outgrows its capacity [3].

Up to this point, digital therapy is mostly used to supply psychotherapy [4] and Healthentia can be used to provide such services as it incorporates all the aforementioned tools, aspiring to effectively support also other diseases than mental health conditions. Healthentia can provide feedback and in combination with a virtual coaching service, orchestrated by a predefined digital clinical pathway, it can create a personalized approach to improve someone’s health. However, it is important to always take into account patients’ mental health needs, as in some cases in-person therapy may be required.

References

[1] “Global Digital Therapeutics Market Report 2022: Analysis & Forecasts 2020-2026 – Market to Reach $12.1 Billion by 2026” (accessed May 15, 2023).

[2] C. Moore, “What Is Digital Therapy and How Does It Really Work?”, Quenza, Aug. 13, 2021. (accessed May 15, 2023).

[3] “Digital Therapeutics: How Software Can Treat Diseases” AltexSoft. (accessed May 15, 2023).

[4] A. Nwosu, S. Boardman, M. M. Husain, and P. M. Doraiswamy, “Digital therapeutics for mental health: Is attrition the Achilles heel?”, Frontiers in Psychiatry, vol. 13, 2022, Accessed: May 15, 2023. [Online].

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CATEGORY: eHealth, patient reported outcomes, e-clinical platform, smart eHealth

SOURCE: Frontiers Comp. Sci., 16 December 2021;  BOOK DOI Link, Chapter DOI Link

Digital Therapeutics: Virtual Coaching Powered by Artificial Intelligence on Real-World Data

Harm op den Akker ; Miriam Cabrita ; Aristodemos Pnevmatikakis ^*

Innovation Sprint, Brussels, Belgium 
Abstract

An ever-increasing number of people need to cope with one or more chronic conditions for a significant portion of their life. Digital Therapeutics (DTx) focused on the prevention, management, or treatment of chronic diseases are promising in alleviating the personal socio-economic burden caused. In this paper we describe a proposed DTx methodology covering three main components: observation (which data is collected), understanding (how to acquire knowledge based on the data collected), and coaching (how to communicate the acquired knowledge to the user). We focus on an emerging form of automated virtual coaching, delivered through conversational agents allowing interaction with end-users using natural language. Our methodology will be applied in the new generation of the Healthentia platform, an eClinical solution that captures clinical outcomes from mobile, medical and Internet of Things (IoT) devices, using a patient-centric mobile application and offers Artificial Intelligence (AI) driven smart services. While we are unable to provide data to prove its effectiveness, we illustrate the potential of the proposed architecture to deliver DTx by describing how the methodology can be applied to a use-case consisting of a clinical trial for treatment of a chronic condition, combining testing of a new medication and a lifestyle intervention, which will be partly implemented and evaluated in the context of the European research project RE-SAMPLE (REal-time data monitoring for Shared, Adaptive, Multi-domain, and Personalised prediction, and decision making for Long-term Pulmonary care Ecosystems).

Keywords: digital biomarkers, machine learning, ai clinical trials, Healthentia, real-world data, e-clinical platform

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