Abstract
As daily life digitalisation comes of age, it also transforms how trial participants contribute
to clinical research. If properly designed, developed, implemented and used, patient-
directed digital tools can significantly increase patient and healthy volunteer safety, ease
trial procedures for them, and improve the quality and integrity of the data and conclusions
derived from the clinical trial. Impressive progress and implementation is seen in the areas
of participants’ information, engagement and training, in communication with the trial team,
in the use of wearables, apps and other devices to collect endpoints, monitor compliance
and ensure safety, and with trial finding and recruitment. Digital progress, however, comes
with a price as specific expertise may be crucial, system and process set-up can require
substantial investment, and data safety and protection demands a high level of diligence.
Introduction
Digitalisation has transformed all aspects of daily life [1]. Medical therapy, health and
clinical care are key areas of the digital revolution [2]. The Springer Nature group offers a
dedicated publication platform on digital health, the BMC Digital Health Journal [3]. While
clinical research, as a highly regulated field, is rather conservative as regards introduction of
new methodology, use of digital tools in clinical trials has become standard practice and is
acknowledge by Regulators like the FDA and EMA [4,5]. Digital technology in a clinical trial
not only is part of its operational infrastructure [6] but also has important implications for
the trial participant who is, except in Phase 1 Healthy Volunteer trials, a patient.
Patient centricity, i.e., having the perspective of the patient in mind for all aspects of a
clinical trial, nowadays is regarded as a cornerstone of successful clinical research [7].
Digital technologies can significantly support the move towards more patient-centric
clinical trials [8]. The following review provides an overview over some areas of patient-
centric digital technologies in clinical research.
Review
Information management, participant engagement, training and communication
Informed Consent requires adequate information of the person who shall decide on
consenting or not. The potential trial participant must have understood all relevant aspects
of the clinical trial, and all questions she or he may have must have been satisfactorily
answered. Even if personal interaction with the trial team and the investigator is the most
important aspect of the information process, digital technology can provide significant
supplementary support. Virtual technology, including but not limited to videos, interactive
tools, gamification and augmented reality, increases learning efficiency [9]. In addition, it
offers the opportunity to provide remote access to information [10]. Most commercially
available eConsent software includes virtually enhanced learning options. YPrime states
that their eConsent solution helps “patients to understand complex material at their own
pace” [11]. Florence’s eConsent is promoted as “easy for you and your participants with
secure, efficient and fully digital workflows for clinical trials” [12]. The Swedish company
Clinical Trial Consultants offers an eConsent which includes videos and/or digitalised
documents, pictures and instructions, where the investigator can also inform about the
study during a telephone or video meeting [13]. Patient-centric eConsent based on remote
video visits, engaging participants “in the comfort of their home” which “reduce(s)
complexity and increase(s) your patient’s experience” is promoted by Castor [14]. Advarra’s
eConsent is “designed to enhance participant engagement while ensuring regulatory
compliance”. It contains interactive multimedia tools and verifies comprehension [15].
Medidata offers a “patient-friendly” eConsent with direct connection to their Electronic
Data Capture technology [16]. While eConsent offers a fully remote process of trial
participant information and consenting which may be convenient for many patients who live
far from a clinical site, the lack of face-to-face personal interaction is controversial. Ethical
Committee members may consider that direct contact ensures better understanding and
informed decision-making. Furthermore, in some countries like Switzerland, wet ink is still
seen as more reliable than electronic signature as it comes to Informed Consent in clinical
trials [17].
Comprehensive understanding of all aspects of the clinical trial is not only essential in
preparation for the consenting decision but remains a crucial part of patient engagement
throughout the clinical trial. Quality of data collection and trial participants’ retention can be
substantially improved through use of AI-assisted video monitoring. Videra Health claims
that real-time video, text, and audio assessments can detect subtle changes in health and
behaviour. Interaction through remote video is expected to ensure better trial experience
and foster patient engagement [18]. Gamified adherence trackers have the potential to
further enhance trial participant compliance with the trial requirements and their retention
[19]. Even though it comes after finishing participation, patient-focussed communication of
trial results is a crucial part of participant engagement. Transparency creates trust and
willingness to join, both at time of consent of an individual patient and for future
participants. Publication of lay language trial results are a legal requirement in the EU [20].
User-friendly and patient-facing tools like MyStudyManager [21] allow trial participants to
get study updates and alerts in real time. The TransCelerate initiative, a collaborative
initiative of a large number of research-based pharmaceutical and biotech companies have
developed a resource pack with recommendations regarding digital tools enabling individual
participant data return [22].
Communication between the clinical trial site and the participant can be facilitated by
numerous digital tools. Like in medicine in general, telemedicine in clinical trials is on the
rise, with impact on all relevant aspects of the trial, including trial design input, screening
and recruitment, the Informed Consent process, patient monitoring, communication,
education and training, and surveillance of patient safety and compliance [23]. Virtual trial
platforms offer easy-to-use communication and interaction technologies [24, 25,26] which
introduce more and more elements of decentralization in clinical trials.
Study endpoints, participant compliance, patient safety
Accuracy and precision of wearables have significantly increased over the past decade.
While in many circumstances such technology may not yet be sufficiently reliable to fulfil
the strict quality requirements for primary endpoints in pivotal trials, they may be used for
secondary endpoints or in exploratory phase 2 trials. Wearables and sensors can replace
invasive measurements and may be more convenient for patient use. Remote transmission
technology reduces the frequency of trial participants in-person visits at the clinical trial
site. A huge number of different physiological parameters meanwhile can be detected by
non-invasive sensors and be used in exploratory clinical trials. Cardiovascular and
respiratory parameters measured by wearables and used in clinical trials include heart rate
(e.g., RATE-AF trial [27]), heart rate variability (trial examples [28,29]) and other
electrocardiographic parameters, blood pressure (trial example [30]), pulse wave velocity,
blood oxygen saturation, respiratory rate, breathing patterns, end-tidal CO2 and oxygen
consumption (VO2). Furthermore, many metabolic parameters like glucose including non-
invasive continuous glucose monitoring (CGM) (trial example [31]), lactose, electrolytes (for
sweat analysis) or alcohol are amenable to non-invasive sensors. Based on algorithms, skin
sensors estimate core body temperature from skin temperature. Electrodermal activity can
be used as a proxy for sympathetic activity. Sleep quality, based on duration of the sleep
stages light, deep and REM (rapid eye movement) are estimated based on heart rate, heart
rate variation, movement and SpO2 (e.g., SLEEP-1 trial [32]). Consumer headbands (Muse,
Dreem) can record brain waves (electroencephalography, EEG). An FDA-approved wearable
allows detection of impeding seizures based on accelerometer and heart rate analysis
(Empatica Seizure detection [33,34]). Accelerometers with gyroscopic features detect
posture abnormalities and falls. The digital biomarkers usually are derived from smart
algorithms which themselves use a (limited) set of physiological measurements. As an
example, the Empatica wearable assesses within one device more than 100 digital
biomarkers, including blood oxygen saturation, temperature, pulse rate, pulse rate
variability, respiratory rate, actigraphy, and sleep detection [35].
Patient-reported outcomes (PRO) are increasingly assessed in clinical trials. Medical
treatment success must not be restricted to physiological measures, even not only to hard
endpoints like disease-free intervals or survival but should be considered relevant by the
patient themselves [36]. While traditionally PROs were collected on digital devices provided
by the trial sponsor, PRO software has been developed which can be installed on the trial
participants’ own device (“Bring Your Own Device” = BYOD). BYOD methodology may
decrease patient burden and improve data quality [37]. Even though few cases have been
published where PROs were assessed through BYOD, it seems that quite some experience,
including regulatory acceptance, is available at individual sponsors [37]. Commercially
available examples of BYOD PRO technology include e.g. Medable [38], Science 37 [39] or
Clario [40].
Due to their strict inclusion and exclusion criteria, clinical trials reflect only a minority of the
patient group who later on, once the drug under development is marketed, are treated with it
[41]. Despite various efforts to broaden the criteria [42], the clinical research dilemma has
little changed over the past 20 years: patient-centricity of pre-approval drug development is
largely restricted to the group of patients actually studied. Integration of Real-World-Data
has emerged as a powerful tool to address the problem. Real-World-Data bring the totality
of patient experience into clinical research and, as a bystander effect, may reduce the
number of trial participants needed to include. Regulatory authorities support its use and
provide guidance how to integrate the data without compromising scientific validity [43,44].
Real-World-Data can be commercially purchased through companies like e.g. IQVIA [45] or
Cytel [46] alongside Optum [47], Oracle Health [48], ICON [48], Castor [49] and many
others. PatientsLikeMe [50] was initially launched by the family of an ALS (Amyotrophic
Lateral Sclerosis) patient in 2005. After having opened up for all diseases, it now claims
helping people living with any health condition to connect with peers, learn together and
take charge of their health. Today, PatientsLikeMe it is a platform where over 850.000
members exchange experience and also inform on recruiting clinical trials. PatientsLikeMe
is technically supported by a company called Fuze Health [51] which also offers services of
several remote pharmaceutical and diagnostic providers.
Patient compliance in clinical trials includes reliability of study drug intake but goes far
beyond that. Trial participants are active contributors to multiple safety, quality and efficacy
aspects of a clinical trial. Their accuracy and precision in complying with study procedures
is of paramount importance. Remotely usable digital tools can significantly support patient
compliance. Video Directly Observed Therapy (vDOT) or Video Observed Therapy (VOT)
evidently enable direct visual contact between a member of the trial team and the
participant, setting the frame for direct and indirect surveillance as well as offering support
in correctly handling study drug or assessing endpoints. The technique can be based on
smartphone, tablet or computer. Outside clinical trials, vDOT has been successfully
employed in assuring adherence during long-term treatment of tuberculosis and increasing
patient satisfaction [52]. Beyond its primary purpose of ensuring compliance, vDOT has the
potential to empower patients, thus making them competent actors of their own health care
[53]. Video Directly Observed Therapy was successfully used also with children and
adolescents [54]. It is obvious that the technique opens a large promise for use in clinical
trials. Video observation can be combined with an AI-enabled algorithm. Patient adherence,
e.g. with study drug intake, is video assessed through use of a smartphone and
subsequently analyse by an app installed on the device. Subsequently, only the analysis
result – e.g., confirmation of correct drug administration – is transferred to a central server
which avoids issues of data privacy related transfer of identifiable face images [55]. The
technique was successfully used in a clinical trial investigating a new schizophrenia medical
treatment [56]. Another example is Videra Healths AI-Assisted Remote Patient Monitoring
tool [57]. Based on video, text and audio check-ins, patients and their health status can be
remotely monitored. The close interaction benefits both sides. While the health care
provider – or, in a clinical trial, the investigator and site staff – can maximise oversight and
ensure treatment adherence or protocol compliance, the patient or trial participant is
motivated by personal contact, has access to information sources and ultimately enjoys
empowerment and satisfaction.
The main purpose of a clinical trial is to establish safety and efficacy of an innovative
treatment. Safety assessment in clinical trials is mainly based on collection and analysis of
adverse events and laboratory results and runs under the designation Pharmacovigilance.
While during clinical development all adverse events – irrespective of whether they are
considered drug-related or not – are considered, Pharmacovigilance in spontaneous post-
marketing assumes at least possible drug-relationship and thus assesses adverse effects.
Various methodologies have been proposed to improve recollection of adverse events in
clinical trials – as those often are not reported during participants’ visits – from simple
written to more convenient mobile diaries for symptom tracking. Getov e.a. [58] reviewed
remote digital tools to improve monitoring of adverse events. While they focus on post-
marketing safety surveillance, the same applications and solutions can be implemented
into clinical trials and offer a more patient-centric approach of Pharmacovigilance.
However, adverse event frequency assessment must stay within-trial, as such mobile
diaries evidently will inflate the number of reported adverse symptoms and events [59]. In a
monocentric cancer trial, patients recorded almost twice as many different symptoms
through the mobile application compared to conventional health care provider assessment
[60]. Similar results were shown for oncology patients in multicentre trials who, when
allowed to self-assess adverse events, reported twice as many grade 2 events of
constipation, fatigue, rash on hands and feet or nausea than did investigators [61]. However,
the potential to give real-time alerts represents an additional, patient-centric safety feature
of mobile symptom tracking – described as “a mobile app that saves lives” [62,63]. Remote
adverse event surveillance in real-world healthcare has gained much interest [64]. It may be
conceived as less urgent in clinical trials where patients are very closely surveyed by the
investigator and site team. However, it can be safely assumed that the opportunity to self-
report adverse events will increase treatment adherence and protocol compliance,
especially in ambulatory clinical trial patients. Furthermore, digitally enhanced
Pharmacovigilance can support side effect assessment beyond the sampling of adverse
events and laboratory abnormalities. Artificial intelligence enabled visual symptom mapping
offers the opportunity to visualize patient experience in clinical trials. Graphical tools allow
trial participants to mark symptoms on a body diagram or other representative figure, e.g.
tick box areas of pain on a digital display like with Michigan Body Map (MBM) [65]. Machine-
learning supported hierarchical clustering of patient-reported pain distribution on digital
body maps drawings revealed significant fibromyalgia underdiagnosing [66]. Whether such a
tool would be usable in assessing endpoint analysis in clinical trials, i.e., not only being
superior in diagnosis but also in detecting treatment effects, remains to be shown. Similarly,
rash progression in atopic dermatitis can be digitally assessed [67]. Clinical trials may use
such digital, patient-engaging solutions to track disease development and assess outcome
measures.
Clinical trial finders and eligibility assessment
For the patient and potential trial participant, a primary and often difficult challenge is to
find a suitable clinical trial. Not all patients, especially not those outside oncology and life-
threatening or chronically disabling diseases, have direct access to a clinical trial centre
where a trial which fits their disease characteristic and status, and matches the patients’
expectation and situation can be identified. Over the past decade, patient-oriented clinical
trial platforms have gained much attention as clinical trial finders. However, user
friendliness varies, and not all digital applications offer customized trial proposals. The
number of online recruitment platforms is large and still increasing. For the internationally
active digital solutions, culturally adapted design and presentation are important, as
preferences vary substantially between cultures and regions [68]. Cultural customization
may be especially important for minoritized groups [69].
Examples of recruitment platforms include e.g. Antidote [70], TrialScreen [71], ClinicalNet
[72], Mytrials [73], Trialx [74] and the WHO’s International Clinical Trials Platform [75]. The
Clinical Trials Map [76] uses data from the ClinicalTrials.gov registry [77]. Additional patient-
oriented trial finders are referenced in the section on recruitment services. Caution is
advised for patients who endeavour on digital trial search without professional or
experienced support. As an example – in August 2025, when the author entered the
condition “migraine” as well as some personal identifiers like address, age and gender, into
one of the platforms, the tool suggested seven trials, none of which investigated migraine or
a related condition. Instead, it directed to trials addressing a set of very mixed diagnoses,
specifically spondylarthritis, diabetic neuropathic pain, Long de Novo lesions, primary
hypercholesteremia, coronary artery disease, distal sensory neuropathy and advanced
cancer.
Several pharmaceutical companies offer their own trial platform [78,79,80,81,82] where
trials sponsored by the respective firm can be found. The European Medicines Agency EMA
[83] and the US National Institute of Health NIH [84] have set up platforms where patients
and caregivers can search for clinical trials. The above-mentioned US clinical trial registry
ClinicalTrials.gov is one of the most complete trial platforms. Regulator or government
supported platforms as well as those offered by large pharmaceutical companies often are
more reliable than the freely offered private company tools. However, the former usually
lack user-friendliness, while the latter offer only a restricted set of trials.
Thus, for many patients, it may be better to ask their treating physician for help. Health care
providers may use trial finder platforms specifically set up for them, like Trialing [85] which
provides trial information to health professionals on more than 4000 clinical trials in 26
countries. A great number of recruitment support solutions exist which primarily address
the sponsor and offer help in finding the right patients. While here the approach is not
directly patient-facing, these tools nonetheless take the patient perspective into account
and diligently integrate individual markers and characteristics into the matching endeavour.
Medidata claims to center their digital solution landscape around the patient [86]. An end-
to-end solution to “find, educate, engage, and enroll clinical trial participants worldwide” is
promoted by Citeline [87]. In fact, the clinical trial recruitment support business is booming.
Sano Genetics, a Cambridge University spinout health company, lists 20 clinical trial
recruitment companies [88]: their own Sano Genetics [89] which aims at bridging patients
and researchers through a patient-centric digital platform; OneStudyTeam [90] that holds
StudyTeam, a cloud-based platform primarily supporting patient recruitment; Science37
[91], a US-based company which specializes on decentralized clinical trials [39] and claims
to have over 570.000 patient relationships; THREAD Research [92] who offer a decentralized
trials platform which also supports recruitment; Elligo Health Research [93] who claim to
have access to millions of patients through hospital and major health service cooperations;
Carenity [94], part of the German EvidentIQ Clinical Data Science group with more than
500.000 digital contacts to patients and caregivers across 1.200 medical conditions;
Embleema [95] whose tool integrates data from more than 60.000 health care centres and
more than 550 wearables, Curebase [96] who provide an end-to-end eClinical platform and
virtual site network which enables patient screening and eligibility evaluation; PatientWing
[97] who address both, patients looking for a clinical trial as well as sponsors seeking
recruitment support; BBK Worldwide [98] with a range of services not only including patient
recruitment but continued education and engagement; Clara Health [99], a patient-oriented
study finder; StudyKik [100], a Syneos Health company who supports patients and offers
various services to sponsors; Clariness [101] who are active in more than 50 countries and
have access to more than 8.000 sites; CSSi [102], an Elixia company who claims to be an
industry leader in delivering patient recruitment and enrolment strategies; Antidote [70] who
address both patients and sponsors (see above); ClinicalConnection [103] who state that
they have over a million members, with focus on the US; TrialX [74], a trial finder for patients
(see above); Autocruitment [104] who specialize on patient recruitment services for
sponsors; Trialbee [105] who claim that their technology ensures “hyper-targeted” patient
recruitment; and MMG [106] with a patient screening record of more than 1.000.000 patients
since 1987. The list is definitely incomplete; furthermore, the company landscape is rapidly
changing with takeovers and fusions. Some of the above-mentioned service providers offer
recruitment services as part of an overall trial support business, others restrict their
activities and technical solutions to recruitment, often combined with participant retention
and engagement activities. Many of them use AI-powered technology to support the digital
processes. While all of them claim patient-facing focus, it is obvious that the processes rely
more on data management techniques than personal interaction.
The latter is increasingly becoming amended by technical solutions as well – namely,
patient chat-bots who replace the costly personal interaction between a patient who is
looking for a clinical trial, and a health care provider who can help identify a suitable study
and explain participation burden, associated risks and potential benefits. Eligibility chatbots
engage patients in a conversational format, asking them about their medical condition,
demographics, treatment history, and other relevant health information. Instead of requiring
patients to read through long eligibility criteria documents, the chatbot translates questions
into simple, patient-friendly language. It uses predefined rules (derived from inclusion and
exclusion criteria) or AI-driven models to assess whether the patient might qualify for a given
trial. Based on the responses, the chatbot filters available clinical trials and identifies which
ones the patient may be eligible for. If the patient is potentially eligible, the chatbot provides
details about the trial, such as purpose, duration, location, and contact info. Some
advanced systems can even connect patients directly to research coordinators or allow
them to start the enrolment process. Hospitals and research organizations (e.g., NIH,
Cancer Research Institutes) use such chatbots to recruit participants. Clinical trial sponsors
or CROs may integrate eligibility chatbots on their websites to increase trial enrolment
efficiency. A concrete example of a clinical trial eligibility chatbot is the ChatGPT-powered
AskFiona AI by Massive Bio [107] which specifically addresses oncology patients.
Discussion and Conclusion
Patient-facing digital solutions are a two-edged sword. On the one hand, they open the field
for a large array of convenience and comfort, and they offer huge increases in availability of
information, training tools and virtual connectivity. On the other hand, direct inter-personal
communication is more and more replaced by virtual interaction which, as most visibly
demonstrated by human-imitating chatbots, creates an impression of human contact but
sooner or later is demasked as technical tool which ultimately may represented an ethical
issue of human respect [108].
While technical achievements regarding patient-facing digital solutions are impressive, from
a regulatory perspective they may not always fulfil quality expectations or considerations of
legal validity. As already mentioned [17], eConsent including electronic signatures is not
universally accepted. Informed Consent based on virtual interaction alone is insufficient –
personal interaction with a competent trial team member is still required. Ethics committee
representatives, investigators, regulators, and patient organizations across EU Member
States highlight that eConsent is intended to support, not replace, personal interaction
[109]. While decentralized elements are more and more included into clinical trials, fully
decentral conduct, i.e., without patient visits at the clinical trial site, does exist but is more
an exception than an upcoming rule. Such trials bring along a substantial operational
burden and will require an overall change of health care management before being broadly
implemented [110]. However, large pharmaceutical sponsors are engaged in bringing
patient-facing virtual trials forward [111,112].
Wearables have found their way into many aspects of patient care, with a focus on self-
administration by patients. However, validation requirements for their use as endpoints in
clinical trials are rarely fulfilled. In the realm of the strict regulation of clinical research,
wearables need to meet rigorous fit-for-purpose validation, yet consumer-grade devices
frequently fall short, as they rely on proprietary algorithms that are not transparent or
clinically validated. Validation of wearables for use in clinical trials requires full
development of their usability [113,114,115].
Trial finders for patients as well as recruitment support technology for sponsors offer huge
opportunities through access to high numbers of patient records. However, the quality of
the Electronic Health Record (HER) data used by most of the solutions may often be
insufficient to guarantee a matching of trial and participant as EHRs have well-known quality
deficiencies like incompleteness, inaccuracies, lack of standardization, bias (like
underrepresentation of some populations), and historicity (data are from the past), and
generally accepted guidelines on how to use them are lacking [116]. In addition, there is a
conceptual caveat in that digitized patient (or trial) finders operate on an a priori anonymous
basis. The patient to whom a trial site is proposed, or who is contacted by a recruitment
tool, usually does not have a personal relationship or experience with the respective trial
staff. However, the decision to participate in a given clinical trial much depends on a
trusting personal relationship with the investigator [117]. While it could be argued that trust
alone never should be sufficient to motivate a trial participation decision, it undisputedly
remains a crucial element of an ethically sound consent process, and further on has a
supportive effect on patient retention.
Last not least, all digital patient-facing tools come with a caveat on personal data
protection, as by definition they use sensitive health information. The risk of personal health
information leakage should not under-, but also not be overestimated. In some contexts
(especially private health, life, disability, or long-term care insurance), insurers actively look
for indications of chronic health problems and may refuse or restrict coverage if such
becomes known to them. In most countries however, even life insurance companies cannot
legally search for health information on candidates without their consent or refuse
insurance if a hint on chronic health problems is found by illegal means (for the US, see
HIPAA [118]). In some regions, specific data protection rules like e.g. the EU’s General Data
Protection Regulation may prohibit cross-border transfer of sensitive personal information,
like e.g. face videos unless specifically agreed by the patient [119].
In conclusion, digital patient-facing tools in clinical research are a rapidly growing field
which carries much promise. When handled with care and consideration, these
technologies can improve access to clinical trials, ease communication, enhance patient
empowerment, increase trial participant safety, and add precision and relevance to
outcome measures. They then serve the purpose of ethically sound, safe and efficacious
clinical trials, capable of improving health care and ultimately serving the patient.
Foodnotes
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