Telix Accelerates Artificial Intelligence (AI) Development Program with Acquisition of Dedicaid

Melbourne (Australia) | 27 April 2023

Telix today announces the expansion of its artificial intelligence (AI) capability with the signing of an agreement to acquire Vienna-based Dedicaid GmbH (Dedicaid), a spin-off of the Medical University Vienna.

Dedicaid’s core asset is a clinical decision support software (CDSS) AI platform capable of rapidly generating indication-specific CDSS applications from available datasets, for use with positron emission tomography (PET) and other imaging modalities. Each CDSS application is trained to predict outcomes such as the severity of disease, risk to the patient and/or inform treatment decisions.

The AI platform is also favourably differentiated from commercially-available AI solutions currently used in PSMA-PET imaging, which are limited to supporting clinicians in the interpretation and reading of images – without a prediction capability. This differentiation is driven by the Dedicaid developed AutoML (automated machine learning) engine behind the AI platform, effectively meaning it is a “zero code” solution. This greatly reduces the time, cost and level of expertise required to build, test and validate new CDSS applications, facilitating a streamlined development and regulatory pathway for each new application.

The technology has been developed by Dedicaid in collaboration with the Medical University Vienna, with proof of concept on the machine-learning methodology and applications developed for prostate, breast and lung cancer published in leading peer-review journals.[1]

The acquisition accelerates the development of Telix’s AI platform – denoted as Telix AI™ – by adding predictive capabilities alongside the imaging analysis module, being developed in partnership with Invicro LLC,[2] which automates the classification of lesions to support greater efficiency and standardisation in the imaging workflow. 

This acquisition will give Telix the ability to rapidly generate CDSS applications that are highly complementary to the Company’s radiopharmaceutical pipeline. Following completion of the transaction, Telix aims to finalise validation activities and regulatory submissions (United States Food and Drug Administration (FDA) 510(k) and CE Mark (Europe)) for the AI platform as a ‘software as a medical device’ during 2023.

Dr Michael Wheatcroft, Chief Scientist at Telix said, “AI adds a new dimension of support to the clinician and patient by using data generated through medical imaging to facilitate timely and effective clinical decision making. This acquisition provides Telix with a powerful AI development platform that greatly enhances our ability to rapidly generate new applications from clinical imaging data.  These applications have the potential to assist clinicians in predicting disease progression and treatment response, thus supercharging and differentiating Telix’s AI offering. It is also intrinsically aligned to the philosophy behind theranostics – which is to use the insights from medical imaging to inform and guide an optimal treatment pathway.”  

Thomas Beyer, Co-founder and CEO of Dedicaid and Head of the Research Domain ‘Quantitative Imaging and Medical Physics (QIMP)’ of the Medical University Vienna said, “We have built the Dedicaid platform with the mission of enriching medical imaging with artificial intelligence in order to help clinicians navigate the complex task of diagnosing and treating cancer and deliver state-of-the-art patient care. After extensive research and validation, we are excited that Dedicaid will now become a part of Telix to complete the transition of this technology to commercial stage.”

Following the acquisition, Telix will have ownership of all intellectual property related to the Dedicaid AI Platform.

To read the full ASX release click here

To download the accompanying presentation click here

[1] Papp, L et al. Journal of Nucl Med. 2018; Papp, L et al. European Journal of Nucl Med and Mol Imaging. 2021; Zhao, M et al. European Radiology. 2022; Krajnc, D et al. Cancers. 2021; Papp, L, Journal of Nucl Med. 2019.

[2] Telix media release 14 June 2022.