Summary
Each year an estimated 40M people suffer from Alzheimer’s disease (AD) globally, and a new case is diagnosed every 4 seconds, leading to a substantial socioeconomic burden of over €800B annually. Despite this large need, currently there is no cure available for AD. Moreover, the clinical trial failure rate for novel AD therapies being tested is over 99%. Every failed trial leads to large financial losses for the trial sponsor, and as a result there is an urgent need to reimagine AD clinical trial design.
Recently, there has been a paradigm shift in the design of AD clinical trials, with most new trials now focusing on enrollment of Prodromal AD (P-AD) patients. However, patient recruitment in the P-AD stage is challenging as current methodologies (PET, MRI) lead to a large number of false positive and negative cases. As a result, optimal stratification of P-AD patients during clinical trial recruitment, remains an unmet market need.
To meet this market need, ADmit Therapeutics, an innovative diagnostics SME, aims to deliver MAP-AD: an automated epigenetic analysis platform for accurate prediction of progression status of P-AD patients. The MAP-AD platform relies on novel machine learning algorithms that can identify specific methylation patterns in mitochondrial DNA (mtDNA) isolated from the blood samples of P-AD patients. This allows for a rapid and accurate selection of patients to be enrolled into a clinical trial independent of Aβ status, for the first time.
During this EIC Accelerator project, we will finalize the development of our predictive algorithms together with a dedicated software interface, and perform clinical validation in collaboration with our hospital partners to deliver a finalized platform that is ready for commercial launch. We have a strong network of partners such as Bellvitge University Hospital, Hospital Clinic de Barcelona, CITA-Alzheimer, Hospital Moisès Broggi, Hospital General de l'Hospitalet, Janssen, Roche who will be the early adopters of MAP-AD.
Recently, there has been a paradigm shift in the design of AD clinical trials, with most new trials now focusing on enrollment of Prodromal AD (P-AD) patients. However, patient recruitment in the P-AD stage is challenging as current methodologies (PET, MRI) lead to a large number of false positive and negative cases. As a result, optimal stratification of P-AD patients during clinical trial recruitment, remains an unmet market need.
To meet this market need, ADmit Therapeutics, an innovative diagnostics SME, aims to deliver MAP-AD: an automated epigenetic analysis platform for accurate prediction of progression status of P-AD patients. The MAP-AD platform relies on novel machine learning algorithms that can identify specific methylation patterns in mitochondrial DNA (mtDNA) isolated from the blood samples of P-AD patients. This allows for a rapid and accurate selection of patients to be enrolled into a clinical trial independent of Aβ status, for the first time.
During this EIC Accelerator project, we will finalize the development of our predictive algorithms together with a dedicated software interface, and perform clinical validation in collaboration with our hospital partners to deliver a finalized platform that is ready for commercial launch. We have a strong network of partners such as Bellvitge University Hospital, Hospital Clinic de Barcelona, CITA-Alzheimer, Hospital Moisès Broggi, Hospital General de l'Hospitalet, Janssen, Roche who will be the early adopters of MAP-AD.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/960327 |
| Start date: | 01-01-2021 |
| End date: | 31-03-2024 |
| Total budget - Public funding: | 3 568 650,00 Euro - 2 408 055,00 Euro |
Cordis data
Original description
Each year an estimated 40M people suffer from Alzheimer’s disease (AD) globally, and a new case is diagnosed every 4 seconds, leading to a substantial socioeconomic burden of over €800B annually. Despite this large need, currently there is no cure available for AD. Moreover, the clinical trial failure rate for novel AD therapies being tested is over 99%. Every failed trial leads to large financial losses for the trial sponsor, and as a result there is an urgent need to reimagine AD clinical trial design.Recently, there has been a paradigm shift in the design of AD clinical trials, with most new trials now focusing on enrollment of Prodromal AD (P-AD) patients. However, patient recruitment in the P-AD stage is challenging as current methodologies (PET, MRI) lead to a large number of false positive and negative cases. As a result, optimal stratification of P-AD patients during clinical trial recruitment, remains an unmet market need.
To meet this market need, ADmit Therapeutics, an innovative diagnostics SME, aims to deliver MAP-AD: an automated epigenetic analysis platform for accurate prediction of progression status of P-AD patients. The MAP-AD platform relies on novel machine learning algorithms that can identify specific methylation patterns in mitochondrial DNA (mtDNA) isolated from the blood samples of P-AD patients. This allows for a rapid and accurate selection of patients to be enrolled into a clinical trial independent of Aβ status, for the first time.
During this EIC Accelerator project, we will finalize the development of our predictive algorithms together with a dedicated software interface, and perform clinical validation in collaboration with our hospital partners to deliver a finalized platform that is ready for commercial launch. We have a strong network of partners such as Bellvitge University Hospital, Hospital Clinic de Barcelona, CITA-Alzheimer, Hospital Moisès Broggi, Hospital General de l'Hospitalet, Janssen, Roche who will be the early adopters of MAP-AD.
Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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