Precision Medicine Approach to Cell Therapy in Heart Failure

Code

J3-3075 (A) - included in ARIS records

Head

PhD Bojan Vrtovec

Period

10/1/2021 - 9/30/2024

Range in 2023

0.29 FTE

Science

Natural sciences and mathematics (1)
Engineering sciences and technologies (2)
Medical sciences (8)
Other (1)

Reseacher status

Researcher (11)
Junior expert or technical associate (1)

Education

Doctor's degree (9)
Other (3)

Sex

Woman (4)
Man (8)

Status

Employed at RO and RRD (11)
No data on employment in RO (1)

No. of publications

10–99 (2)
100–999 (9)
1,000–9,999 (1)

Projects / Programmes source: ARIS

source: ARIS

Precision Medicine Approach to Cell Therapy in Heart Failure

Research activity

Code	Science	Field	Subfield
3.06.00	Medical sciences	Cardiovascular system

Code	Science	Field
3.02	Medical and Health Sciences	Clinical medicine

Keywords

stem cells; heart failure; precision medicine

Evaluation (rules)

source: COBISS

Evaluation of bibliographic research performance indicators according to ARIS methodology

Points

5,390.75

A''

724.33

A'

1,711.6

A1/2

2,777.32

CI10

9,589

CImax

1,679

h10

40

A1

17.49

A3

7.88

Data for the last 5 years (citations for the last 10 years) on September 15, 2024; A3 for period 2018-2022

Data for ARIS tenders ( 04.04.2019 – Programme tender, archive )

Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases

source: WoS

source: Scopus

source: COBISS

Database	Linked records	Citations	Pure citations	Average pure citations
WoS	437	8,844	8,281	18.95
Scopus	456	11,526	10,773	23.63

Researchers (12)

no.	Code	Name and surname	Research area	Role	Period	No. of publicationsNo. of publications
1.	32516	Vesna Andročec		Technical associate	2021 - 2024	58
2.	37394	Andraž Cerar	Cardiovascular system	Researcher	2021 - 2024	138
3.	31049	PhD Erik Dovgan	Computer science and informatics	Researcher	2021 - 2023	144
4.	24039	PhD Sabina Frljak	Cardiovascular system	Researcher	2021 - 2024	118
5.	08501	PhD Matjaž Gams	Computer science and informatics	Researcher	2021 - 2024	1,708
6.	29523	PhD Anton Gradišek	Physics	Researcher	2021 - 2024	459
7.	32517	PhD Renata Okrajšek	Cardiovascular system	Researcher	2021 - 2024	103
8.	28021	PhD Gregor Poglajen	Cardiovascular system	Researcher	2021 - 2024	336
9.	19345	PhD Miran Šebeštjen	Cardiovascular system	Researcher	2021 - 2024	275
10.	18826	PhD Bojan Vrtovec	Medical sciences	Head	2021 - 2024	488
11.	37784	PhD Gregor Zemljič	Medical sciences	Researcher	2021 - 2024	123
12.	54242	Neža Žorž	Cardiovascular system	Researcher	2021 - 2024	20

Organisations (2)

no.	Code	Research organisation	City	Registration number	No. of publicationsNo. of publications
1.	0312	University Medical Centre Ljubljana	Ljubljana	5057272000	78,445
2.	0106	Jožef Stefan Institute	Ljubljana	5051606000	91,576

Abstract

Background. Despite significant advances in medical and device therapy over the past decades, chronic heart failure represents an increasingly common and debilitating disorder with poor prognosis and high early and late mortality rates. Although the accumulated clinical evidence suggests that cell therapy may be beneficial in different subpopulations of heart failure patients, the results of clinical trials are inconsistent, which makes it difficult to translate the research findings into everyday clinical practice. Objectives. The overall goal of the project is to develop a personalized cell therapy approach to be used as a standard clinical management in a broad population of patients with chronic heart failure. Specifically, the primary objective of the project is to define optimal patient selection criteria, and the secondary objective is to better define the effects of cell dose, cell type, and cell delivery techniques on the efficacy of cell therapy. Methods. The work plan consists of 2WPs. In WP1 we plan to analyze the combined dataset from 6 previous clinical trials conducted by our research group, enrolling patients with chronic heart failure who were treated with cell therapy. By implementation of artificial intelligence analysis on this dataset we aim to define individual patient profiles that will most likely benefit from cell therapy. Artificial intelligence analysis will be based on the analysis of the patient Holistic Health Records. Classification models and clustering models to assess how patients respond to treatment will be based on classical machine learning and various types of neural networks. Patient responder profiles derived in WP1 will then be validated in a prospective randomized clinical trial in WP2. The study protocol will consist of a prospective, randomized double blind, placebo-controlled design. We will enroll 30 patients with heart failure. After enrollment, all patients will receive 5-day stem cell mobilization with G-CSF. Thereafter, patients will be randomly allocated to either active (SC Group) or control group (Controls) in a 2:1 ratio. Patients in the SC Group will undergo apheresis; CD34+ cells will be collected with immunomagnetic selection, and delivered transendocardialy in the target areas defined by electroanatomical mapping. In the Controls, no apheresis or immunomagnetic selection of CD34+ cells will be performed; the patients will receive transendocardial injections of placebo using the same electroanatomical mapping protocol as in patients from the SC Group. Patients will be followed for 1 year. At baseline, at 6 months, and at 1 year we will perform comprehensive patient evaluation. All data on patient evaluation will be transferred to a secure central database and will be analyzed using an integration algorithm at the end of the follow-up period. Expected Results. We expect that the results of the project will yield important data on patient selection, stem cell type and dose, and cell delivery techniques, which will optimize the efficacy of cell therapy in chronic heart failure. Based on these data, we will design a web-based application, which will serve as a tool to help physicians to select optimal patients for cell therapy in everyday clinical settings.