Threats and Opportunities for the Clinical Investigation of High-risk

Medical Devices in the Context of the New European Regulations

L. Pazart

1,2

, S. Pelayo

1,3

, T. Chevallier

1,4

, G. Gruionu

5,6

, P. Mabo

1,7

, Y. Bayon

, F. Barbot

1,9

T. Lihoreau

1,2

, C. Roussel

1,10

, N. Maglaveras

, E. Lekka

, H. A. Ferreira

, I. Rocha

, L. Geris

and C. Lavet

Inserm, Tech4Health, FCRIN F-31000 Toulouse, France

Univ. Franche-Comté, Inserm CIC1431, CHU Besançon, F-25000 Besançon, France

Univ. Lille, Inserm, CHU Lille, ULR 2694, METRICS, F-59000 Lille, France

IDIL- Nimes University Hospital and INSERM IDESP, F-30000, Nimes, France

Krannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN 46202, U.S.A.

INCESA Institute, Faculty of Mechanics, University of Craiova, Craiova 200512, Romania

Univ. Rennes, CHU de Rennes, Rennes, France

Medtronic, Sofradim Production, Trévoux, France

CIC 1429 Inserm, Hôpital Raymond Poincaré APHP, Garches, France

CIC 1415, CHU Tours, Inserm, University of Tours, France

Lab of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Portugal

Lisbon School of Medicine & Cardiovascular Centre, Universidade de Lisboa, Lisboa, Portugal

Biomechanics Research Unit, GIGA In Silico Medicine, University of Liège, Belgium

Keywords: High-risk Medical Device, Medical Device Regulation, Clinical Investigation, EU MDR 2017/745,

Regulatory Science.

Abstract: This position paper analyses the threats from the current situation of the clinical investigation to the

expectations of the new European regulations focusing on high risk medical devices (HRMDs). We present

also some opportunities to improve the feasibility and quality of clinical investigation. In summary,

investigation protocols of medical devices, advised and authorized by the competent authorities, are few and

heterogenous. There is a lack of quality in the existing studies, a lack of methodological knowledge and

consequently high expectations for assistance from those involved in the design of clinical study protocols

on HRMD. Guidance that is specific to the different type of devices is missing. Adaptive designs, pragmatic

trial, usability methods, computer modeling and real world data are gaining more and more traction for

assessing the safety and performance of high risk medical devices from a regulatory view- point.

EVAL-HRMD Project Consortium

1 INTRODUCTION

A series of major scandals have recently eroded

public confidence in the way high-risk medical

devices (HRMDs) are evaluated and monitored. Of

course, these situations have led to the withdrawal of

products from the market and legal actions have

been taken to sanction not only unscrupulous

manufacturers but also the notified bodies who issue

the famous ‘CE marking’ required to introduce new

products on the European market. By the end of

2018, the International Consortium of Investigative

Journalists' ‘implant files’ investigation shed light on

the way manufacturers can obtain the right to market

medical devices in Europe. These situations

highlight the weaknesses and failings of the health

control system for launching and monitoring

HRMDs. And yet, both patients and physicians want

to ensure that knowledge on innovation can

guarantee safe and efficient use of the new product.

New European regulations on medical device

(EU Medical Device Regulation 2017/745) will

come into effect in the spring of 2021. These new

regulations set forth new, improved rules to

strengthen clinical evidence, particularly for

HRMDs for which clinical investigation is

compulsory.

274

Pazart, L., Pelayo, S., Chevallier, T., Gruionu, G., Mabo, P., Bayon, Y., Barbot, F., Lihoreau, T., Roussel, C., Maglaveras, N., Lekka, E., Ferreira, H., Rocha, I., Geris, L. and Lavet, C.

Threats and Opportunities for the Clinical Investigation of High-risk Medical Devices in the Context of the New European Regulations.

DOI: 10.5220/0010382902740284

In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 1: BIODEVICES, pages 274-284

ISBN: 978-989-758-490-9

This regulatory landslide represents a big

challenge for European Health SMEs (some 25,000

companies, representing 95% of the MedTech sector

in Europe) to maintain their competitiveness and

capacity for innovation, with limited internal

resources; especially in clinical trials skills. The

impact of Medical Device Regulation (MDR)

entering into force and the economic crisis linked to

the Covid-19 on the sustainability of these

companies has not yet been analyzed.

Updating clinical evaluation strategy and reports

to meet the new European requirements will require

major efforts for most manufacturers selling on the

EU market. Given the wide range of medical devices

(MD) available on the market and their countless

variations in design features, treatment goals and

targeted patient groups, setting a single standard

study protocol seems unfeasible.

This paper analyses the threats arising from the

current situation to the expectations of the new

European regulations focusing on HRMDs. We

present also some opportunities to improve the

feasibility and quality of clinical investigation.

2 DEFINITION AND

SPECIFICITIES OF HIGH-RISK

MEDICAL DEVICE

Classification of Medical Device is risk based, that

is, the risk the device poses to the patient and/or the

user is a major factor in the class it is assigned.

Three classes are defined, from Class I including

devices with the lowest risk to Class III including

those with the greatest risk (EU Medical Device

Regulation 2017/745). Device classification depends

on the intended purpose of the device, but also upon

indications for use and targeted population. Class III

devices usually sustain or support life, are

implanted, or present potential unreasonable risk of

illness or injury. Examples of Class III devices

include implantable pacemakers and breast implants.

Around 10% of medical devices fall under this

category.

High-Risk Medical devices (HRMDs)

correspond to current class III and implantable

devices. Many tools based on the annex VIII of the

MDR assist in the risk classification (class I, IIa, IIb

or III) of the product. But high risk and class III are

not necessarily totally overlapping. Other devices

may be high-risk and a variety of factors can

participate in the definition of a high-risk medical

device, such as a specific anatomical location for its

use, the implantable nature of the device, the use of

innovative or untested technologies or materials. The

implementation of any device can also be high-risk,

due to:

 the vulnerability of the patient himself (e.g.:

children, pregnancy, chronic disease, aged)

 the difficulty and delicacy of handling

 the operator's dexterity and experience

(including the patient himself, his relatives or

health care staff)

 the material environment in which the act

linked to the device will be performed

 the potential complications of the procedure

performed.

HRMDs have particularities that make the

conduct of clinical investigations difficult, such as

long-term use and unknown interactions with the

human body, the means of explanting and replacing

implantable devices, the human-machine interface,

the management of data-flow generated, etc.

Although these issues are taken into account in

usability standards (IEC 62366-1 and IEC 60601-1-

6) and many methods of Human Factor Engineering

(HFE) have existed for years, they seem to be

underused (BSI 2016).

3 THREATS ARISING FROM

THE CURRENT SITUATION IN

EUROPE

3.1 The Loss of Europe’s

Attractiveness for Carrying out

Clinical Studies

The complexity of the regulatory process for

HRMDs is partly due to a significant fragmentation

of the global market. Namely, many countries have

their own set of rules around the world (Heneghan,

2012). A new device classified into Class III in

Europe may very well be considered a Class II

device according to a 510k procedure without the

need for a clinical investigation in the United States,

which is easier for businesses.

From our analysis (Figure 1) of annual

declarations of interventional studies on the website

clinicaltrials.gov, we note an increase of 16%

worldwide for medical devices over the last five

years (versus 9% for drugs), while Europe is

experiencing stagnation in the number of studies on

medical devices (+ 2%) and a decrease in the

number of studies on drugs (-5%).

Threats and Opportunities for the Clinical Investigation of High-risk Medical Devices in the Context of the New European Regulations

275

Figure 1: Evolution of clinical trials on medical devices worldwide and representative share for the USA and Europe (in %).

Figure 2: Distribution of Clinical trials on Medical Devices in Europe from 2015 to 2019.

Overall, one study on a medical device starts for

every 3 clinical trials starting on a drug. This has

been stable over the last five years worldwide

whereas, in Europe, this ratio which was identical to

the worldwide figure five years ago, is now

approaching a ratio of 1: 2 (3 medical device studies

for 8 drug studies in 2019).

The figure 2 shows how the initiation of

interventional clinical trials for medical devices has

slowed down in the different member states of

Europe (-10% in 2019 compared to the previous

year), and in particular from the year of publication

of the European regulation 2017/745, and the

dropout rate in international competition,

particularly in relation to the US.

3.2 The Current Observation on the

Lack of Quantity & Quality of

Clinical Studies on MD

Moreover, manufacturers have plenty of leeway and

different interpretations in performing or not the

clinical studies required to obtain their CE marking.

Most of them do the clinical evaluation of their

device based on data in the literature and

assimilation with predicates already on the market.

In 2017 the French health authority (ANSM)

registered CE markings for more than 15,293 new

medical devices (44% class II or III CE marks)

while, at the same time, this same authority only

issued 93 authorizations for new clinical trials of

medical devices.

The Iqwig (Independent German Institute for

Quality and Efficiency in Health Care) assessed the

methodological quality of 122 medical device

evaluation study projects submitted to the Berlin

ethics committee from March 2010 to December

2013 (Sauerland 2019). Of these 122 studies, 69%

were planned before marketing and 57% were

randomized controlled trials (RCTs). While only

half of the studies sought to demonstrate the

effectiveness of the medical device, in the other

studies the main objective stated was safety (18%),

performance (12%), patient-related benefits,

feasibility or user satisfaction.

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A European study by Olberg et al. highlights the

low level of evidence and the poor quality of studies

in the files submitted for the registration of HRMDs

with European technology agencies over the 2010-

2015 period (Olberg 2017). Their results concluded

that only 9% of these files had a very high level of

clinical evidence (meta-analysis but most of them

had pooled effect sizes driven up by a few

randomized control trials (RCT) of low-to-moderate

quality) and only 29% had a high level of evidence

(RCT). Overall, 61% of clinical studies had a

moderate to low level of evidence.

3.3 Imprecise Recommendations for

Conducting Adequate Clinical

Studies

The European Commission provides a range of

guidance documents to assist stakeholders in

implementing the regulations related to medical

devices (MEDDEVs guides). These guides promote

a common approach to be followed by the

manufacturers and Notified Bodies involved in

conformance assessment procedures. Revision 4

(MEDDEV 2.7/1 rev.4, June 2016) is more

prescriptive and requires manufacturers to provide

greater quantity and quality of information for

clinical evaluations. The first set of guidelines

(MEDDEVs guides) was recently updated and

clarified by the European Commission’s Medical

Device Coordination Group (MDCG 2020). The

MDCG posted new guidance (during the year 2020)

on clinical evaluation and evidence for devices and

postmarket clinical follow-up plans, representing for

us the basis to be completed by future guidelines

dedicated to HRMD:

However, these MDCG guidelines give general

advice, and miss the operational details needed to

adapt the design of studies and statistical analyses to

the characteristics of innovative technologies. The

most appropriate, least burdensome paths for

gathering clinical data to support marketing approval

for HRMDs are as varied as the devices themselves;

so more operational guidance are needed.

With the exception of a handful of cardiology

devices, available guidelines (from EU directives,

MDCG newly edited guides or national

transcriptions) and ISO/FDIS 14155 remain mostly

vague and imprecise in describing how to conduct a

clinical investigation and consider the clinical

evidence. Instead, the guidelines let manufacturers

choose how to create their clinical study protocols.

The manufacturers in charge of evaluating their

devices are asked to improve the process without

having the keys or knowledge to do so.

Figure 3: Number of guidelines on clinical evaluation of medical device per member state (Brunotte 2020).

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3.4 Heterogeneity of Advice in the

European Member States

In addition, broadly speaking, the MDRs leave the

organization of clinical investigation protocol

assessment and applicable authorization procedures

to the discretion of the Member States. Different

guidelines have been developed by member states

(figure 3, from Brunotte, 2020) but standard

methodologies are lacking. Those who should be

doing clinical studies on HRMDs -first of all,

manufacturers- have little visibility on what should

be done as well as lacking the required resources and

time.

Notified bodies must then request expert advice

to scrutinize manufacturers’ clinical evaluation

assessment report on HRMDs. Expert opinion does

not ensure a high level of clinical evidence and does

not guarantee a high level of reproducibility.

3.5 Regulation Is Uniform Disregards

Technological Characteristics and

the Evolution of the Devices

The same clinical evaluation requirements apply to

an English stick, a wheel chair, a hip prosthesis or a

connected pacemaker. Passive prostheses and active

implantable medical devices cover a large range of

medical applications and patient needs. These two

groups of HRMD exemplify very different R&D

situations.

R&D of passive prostheses, for example, mainly

involves the study of cells, their components,

complex tissues and organs and their interactions

with natural and synthetic materials. R&D of

implanted passive prosthetic devices also involves

developing and characterizing the materials used to

measure, restore, and improve physiological

functioning. These devices include coated stents,

bio-valves, joint replacements and cellular bone

grafts.

A second group is composed of active

implantable medical devices (AIMDs), (European

directive 90/385/EEC), mostly manufactured by

large international companies with considerable

technological resources (such as St Jude, Medtronic

and Becton Dickinson). AIMDs cover many

different clinical applications such as implantable

defibrillators, neuromuscular stimulators,

neuromodulators, cochlear implants and gastro-

intestinal pacemakers. One of the best-known

AIMDs is the cardiac pacemaker, introduced over 40

years ago, to deliver a controlled, rhythmic electrical

stimulus to cardiac tissue. AIMDs have shown an

impressive evolution over the last 20 years, not only

in size and weight (which has been reduced by a

factor of 10) but also in reliability, power

consumption and physiological functionality.

Specific recommendations have been issued from

learned societies of cardiology.

New advances in this type of devices are

expected with embedded algorithms of increasing

complexity, including adaptive stimulation

scenarios, diagnostic functions, data collection and

transmission, as well as remote multiprogramming

through a wireless link. Telemedicine may then

facilitate diagnosis and care over distances and

remote patient monitoring may lead to better home

care e.g. a pacemaker implanted in a patient, the

patient goes home, and the doctor monitors from a

distance. Patients may also access health information

via web portals, accessible anytime, anywhere.

Consequently, the traditional healthcare model of

patients traveling to see their doctor and being

diagnosed and treated inside hospital walls is no

longer the only relevant model.

The MDR does not differentiate between these

different types of devices, despite their different

characteristics and history of development

3.6 The Lack of Consideration of the

Characteristics of HRMDs for

Their Clinical Evaluation

Similar to drug evaluation, regulators around the

world generally prefer evidence from RCTs when

deciding whether to authorize the marketing of new

medical devices. However, RCTs are time

consuming and require significant financial

resources which are often underestimated; this is

particularly dangerous for SMEs with fragile

economic statuses Above all, this type of trials of

medical devices are difficult to perform for a

number of reasons:

 a device implementation is a complex

intervention and the outcomes of the

intervention are generated by the combination

of varied factors involved – e.g. the device, the

clinicians implementing it, the training, the

clinical condition of the patient receiving it, …

 the absence of comparators available on the

market

 the device often evolves during the clinical trial

due to direct feedback from first end-users,

 the difficulty of randomization due to the small

sample size of the target population,

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 the operator (surgeon, cardiologist, radiologist

…) cannot be blinded to the type of device

implanted, and no placebo exists except for

devices that can be switched on and off

remotely, but “sham operations” are almost

never ethical because the patient experiences

the risk of the intervention but no benefit.

Overall, clinical studies on medical devices are

therefore far from systematic to run, and when

carried out, they do not present the level of

excellence (RCTs) expected by regulators to judge

clinical evidence. But is this requirement for level of

evidence really justified for all types of medical

devices?

3.7 New Digital Health Developments

Have Not yet Been Anticipated in

MDR

Nowadays, m-Health (mobile health) apps are

further widening the scope of how health services

can be delivered and, more importantly, these

technological advances are challenging traditional

healthcare services. The vision that emerges from

this is a health continuum (from healthy individuals

to seriously ill patients), and to cope in the

continuum of our lives we need Connected Health.

The Connected Health paradigm covers that

continuum and includes healthy individuals, those at

risk and chronically ill patients. In Connected

Health, individuals are equal partners with the

healthcare professionals and take part in managing

their own health.

p-Health (personalized health) and m-Health

represent these new domains of application for

information technology in the field of healthcare.

Over the next decade it will be a huge challenge to

propose new services to citizens and the right

regulation. These technologies produce data from

real-world settings. In addition to regulations, in

particular with the General Data Protection

Regulation (GDPR), the production and analysis

with AI of big data is actively studied in order to

develop new knowledge that has so far been

unaffordable.

3.8 High-risk Concept Poorly

Conceived in the MDR

Only three quotations of the word "high-risk" appear

in the 175 pages of the MDR, without any definition.

The clinical evaluation and assessment of level

of risk should incorporate all risk factors in the use

of HRMD and human factor issues.

4 OPPORTUNITIES FOR

CLINICAL INVESTIGATION

DESIGN

The European Commission has launched many calls

for projects on computer modeling, usability

methods, real world data processing and innovative

medical devices. Some of these will be useful for the

future.

Progress in computer modeling and simulation

applied to disease management is a European

strength and various Decision Support Systems have

been developed for different medical disciplines.

Through its new initiatives on digital health and care

within the Digital Single Market policy, the

European Commission aims to leverage the potential

of big data and high-performance computing for the

emergence of new personalized prevention methods

and treatments.

The economic aspects will be addressed in

existing European initiatives on the subject (e.g.

TBMED, MedTechHTA, Impact-HTA projects).

4.1 New Methodological Pathway for

Clinical Studies on HRMDs

The most important factor for successful marketing

approval, practitioner adoption, and safe use of

higher-risk medical devices is robust clinical

evidence.

In the United States, computer modeling and

simulation (i.e., in silico methods) are gaining more

and more recognition from regulatory boards for the

evaluation of the safety and performance of medical

devices. For example, from 2002 to 2019 in the

USA, at least 21% of the 565 pre-market approval

(PMA) applications for HRMDs had computational

modeling efforts provided in the Summary of Safety

and Effectiveness Data (Morrison 2018, 2019). For

the past few years, the FDA has been accepting

regulatory files including digital models, adaptive

studies, hybrid trials, real-world data and experience.

The FDA has thus developed numerous general

guides on these subjects to help medical device

manufacturers carry out adequate studies to obtain

their product launches (FDA 2010, 2018, 2020).

Given the shortcomings of the MEDDEV and

MDCG guidelines and of the ISO/FDIS 14155

Threats and Opportunities for the Clinical Investigation of High-risk Medical Devices in the Context of the New European Regulations

279

standards in terms of the expected clinical study

design, further issues concern the following

considerations:

 alternatives to classical randomized controlled

trials, including pragmatic trials and adaptive

design

 alternatives to frequentist approaches

 integration of Human Factors and usability

study methods

 the place of computer modelling and

simulation models (in silico models and trials)

 the use of real-world data with new analytical

capabilities and mathematical models.

 a deal with companies to get real world data

(RWD) generated by HRMD against freely use

of academic simulation models

4.2 Adaptive Methodologies and

Pragmatic Trials Have Been

Developed as an Alternative to the

Classical RCT Design

Even though the legislation, particularly American

legislation with the Food and Drug Administration

(FDA), qualifies adaptive methodologies as

“modern” and “new” methods, a large number of

these concepts are old but have remained unused for

many years especially by the European notified

bodies for MDs evaluation.

Methodologists propose using tracker design

trials (Lilford 2000), sequential trials (Hamilton

2012), ‘Multi-Arm Multi-Stage’ trials (Wason 2014,

Wathen 2017),

pragmatic trial (Ford 2016, Loudon

2015, Thorpe 2009, Simon 2019, Gamerman 2019)

and adaptive trials (Simon 2013, Meurer 2016,

Magirr 2016, Lai 2019) to take technological

evolution into account and accelerate clinical

development and product launching whilst allowing

early terminations (futility/efficacy) or protocol

adjustments (evolution/suppression of an arm).

These trials rely on planned interim analyses which

allow the investigator to glean useful information for

adapting the strategy. They are particularly relevant

to the context of HRMD clinical evaluation.

With adaptive methods it is also possible to

strengthen the clinical evaluation of medical devices

by authorizing the analysis of multiple evaluation

criteria, carrying out several intermediate analyses,

early terminations in the event of inefficacity,

allocating patients to the most promising arms, re-

evaluating the sample-size and, more especially,

redefining the target population. With these methods

it is also possible to combine the early exploratory

phases with the demonstrative phases which may

help to accelerate and optimize the development and

implementation of innovative devices. When certain

centers only use one of the two techniques under

study and do not know the other technique, or only

master one technique and the result is operator-

dependent, it is possible to use a trial based on

expertise or a cluster trial (or a Stepped Wedge

Cluster trial, Barker 2016) to increase the

participation of doctors and the reliability of the

evaluation. When one arm in the study is less

attractive than the other, studies may be carried out

according to a Zelen plan (Zelen 1990) or according

to a complete cohort pattern. These types of trials

introduce flexibility in the attribution of treatments

and allow better acceptability of the randomization

by the patients and also give us the possibility of

adjusting the results to the randomization. Group

sequential design and adaptive sample-size

adjustment are often used to make study durations

shorter and include a smaller number of subjects.

Nevertheless, there has been criticism of these

adaptive designs and it will be important to analyze

the biases and added value of these proposals, their

acceptability by the stakeholders and their

admissibility by the European authorities.

For the past few years, the FDA has been

accepting regulatory files including digital models,

adaptive studies, hybrid trials design, real-world data

and experience (Guetterman 2017, Campbell 2019).

FDA has thus developed numerous guides on these

subjects to help manufacturers of medical devices to

carry out adequate studies to obtain a marketing of

their products (FDA 2010, 2018, 2020).

4.3 Bayesian Approaches May be used

to Implement and Analyze Clinical

Trials

Bayesian approaches give the possibility of

combining prior information before the trial

(previous studies, expert opinion, literature…) and

current information during the trial to formulate or

reformulate decision-making rules (Campbell 2011,

Ribouleau 2011, Wei 2018).

In a Bayesian clinical trial, any uncertainty about

a parameter is described according to probabilities,

which are then updated during data-collection for the

trial. The probabilities are set beforehand based on

previous data and the probabilities are estimated a

posteriori from the data obtained during the trial

(Pennello 2008). There are no statistical tests but the

probability of the treatment under experimentation

being effective has a 95% credibility threshold.

However, it is very important that the a priori

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information used does not over influence the final

result (sensitivity analysis required). The quality of

information supplied a priori is therefore a key

element in the credibility of results.

4.4 Human Factors Engineering

There are a variety of human factors and usability

evaluation methods (Genise, 2002) for all stages of

design and development, from product definition to

final design modifications like cognitive modeling

methods, inspection methods, inquiry methods,

prototyping methods, usability testing etc. Certain

methods use data from users, while others rely on

usability experts. When choosing a method, cost,

duration and appropriateness should be considered.

4.5 In Silico Modelling

The beginning of the 21st century saw the birth of a

completely new way to investigate living organisms

through computer simulations, called in silico

medicine. Over the last 15 years, significant efforts

have been made to build numerical patient models

from multimodal images, for instance, for surgical

planning and image-guided surgery.

Initially released in 2007, the Virtual Family

(https://www.fda.gov/about-fda/cdrh-offices/virtual-

family) is a set of four highly detailed, anatomically

correct whole-body models of an adult male, an

adult female, and two children. The Virtual Family

project was carried out in collaboration between the

FDA and academic or private European partners

from Erlangen, Germany, and Zürich, Switzerland.

Currently, the Virtual Family models are used for

electromagnetic, thermal, acoustic, and

computational fluid dynamics simulations. Examples

of applications of electromagnetic and thermal

simulations are the assessment of the safety of active

and passive medical implants in a Magnetic

Resonance Imaging (MRI) environment and the

evaluation of the safety and efficacy of ablation

devices. Since the end of 2014, the Virtual Family

has been regularly used in medical device

submissions to the FDA.

The Virtual Physiological Human (VPH) is an

initiative developed over the last decade and

supported by the European Commission to create a

computational framework designed to facilitate the

understanding of the integrative function of

molecules, cells, tissues, and organs and, by this, to

construct a multiscale in silico model of the human

physiology (Viceconti 2008). The collective

framework will make it possible to share resources

and observations formed by institutions and

organizations, creating disparate but integrated

computer models of the mechanical, physical and

biochemical functions of a living human body. VPH

is a framework which aims to be descriptive,

integrative and predictive. The framework consists

of large collections of anatomical, physiological, and

pathological data stored in digital format, with

predictive simulations developed from these

collections and services intended to support

researchers in the creation and maintenance of these

models, and also the creation of end-user

technologies to be used in clinical practice.

The validation of in silico clinical trial models

poses relevant theoretical problems. However, these

have been discussed in specialized publications

(Coveney, 2014) and a standardization committee

(ASME V&V-40 verification and validation in

computational modelling of medical devices), which

worked on some codified guidelines (Popelar, 2013).

A key aspect, which was promoted within the

Medical Device Innovation Consortium (Kampfrath

2013), but that emerged again and again during the

Avicenna consensus process, is that of model

credibility. The process to ensure that a predictive

model is indeed accurate in its predictions is

somehow at the center of a paradox. Models are

usually developed to predict things that cannot be

easily measured, so how do we know how accurate

these predictions are?

4.6 Use of Real-World Data

The use of computers, mobile devices, wearables

and other biosensors gathering huge amount of

health data has been rapidly accelerating. These data

hold potential to allow us to better design and

conduct clinical trials and studies in the healthcare

setting to answer questions previously thought

infeasible. In addition, with the development of

sophisticated, new analytical capabilities, we are

able to better analyze these data (Kumsa 2018,

Sherman 2016).

The increasing availability of data generated by

such devices poses challenges regarding

management and data workflows. The use of

artificial intelligence algorithms in medical devices,

can lead to undetermined risks for users, and require

a proper framework for development and validation.

Progress, particularly in computing and AI, data and

wearable accessibility, is often made at a much

faster rate than guidelines and recommendations are

issued.

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281

5 CONCLUSIONS

In summary, investigation protocols of high risks

medical devices, advised and authorized by the

National competent authorities in Europe, are few

and heterogenous. There is a lack of quality in the

existing studies, a lack of methodological knowledge

and consequently high expectations for assistance

from those involved in the design of clinical study

protocols on HRMD. Guidance that is specific to the

different type of devices is missing.

The “new” EU MDR 2017/745 coming into

effect in May 2021, by obliging clinical

investigation and post-market follow-up, offers the

opportunity to develop novel pathways for the

clinical development of HRMDs. In particular, there

is a perceived lack of knowledge and training in

clinical trial skills in European medical device

companies who could greatly benefit from a

clarification of expectations linked to the MDR for

HRMDs..

Nevertheless, the available guidelines (from EU

directives, MDCG new guides or national

transcriptions) remain vague and imprecise, also

many companies are leaving Europe due to the

complexity and imprecision of MDR. They move to

the US where the regulatory pathway is clearer &

faster.

The risks of this situation in Europe are

reinforced by many threats:

 the current observation on the lack of

quality clinical studies,

 the specificities of HRMD by medical

speciality,

 the economic fragility of European HRMD

companies (95% SMEs),

 the high expectations of safety on the part

of patients and healthcare professionals,

 the loss of attractiveness of Europe for

carrying out clinical studies,

 the desire for a "smooth transition" from

directives to MDR without real means.,

 the attribution of a CE marking by various

private structures,

 the diversity of approach from one notified

body to another, and the absence of a

centralized procedure

At both European and national level, before and

after marketing, a new balance needs to be found

between the need for rigorous evidence and the real

world complexity of gathering such evidence; a

balance between strict regulation and high levels of

evidence for high risk medical devices, and the

possibility of other types of evidence for devices

associated to lower levels of risk.

Adaptive designs, pragmatic trial, usability

methods, computer modeling and real world data are

gaining more and more traction in the United States

for assessing the safety and performance of medical

devices from a regulatory view- point. The European

Commission has launched many calls for projects on

these subjects, generating new knowledge and new

teams of experts. Expectations from stakeholders of

clinical investigations tend to bring these experts and

knowledge together to prioritize the methods and

develop useful guidelines for those who wish to set

up clinical studies on HRMDs.

ACKNOWLEDGEMENTS

We would like to thank all those who contributed to

the preparation of the Eval-HRMD project, and

especially Joanna Baranowska, Marine Beaumont,

Regis Beuscart, Patrick Boisseau, Gaelle Brunotte,

Guy Carrault, Jacques Demotes, Marlene Durand,

Maria Dutarte, Jerôme Fabiano, Jacques Feblinger,

Joris Giai, Lucian Gruionu, Gemma Killeen, Amélie

Michon, Alexandre Moreau-Gaudry, Claire Nassiet,

Frédéric Patat, Pierre Pautre, David Orlikowski,

Delphine Smagghe, Dimitar Tcharaktchiev,

Chrystelle Vidal, Sebastian Wawrocki. The project

received a grant from the National Research Agency

to support the networking of partners.

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