Development History

  • 1986

    Development began

    TruScreen’s development began in 1986, driven by two leading medical academics from Sydney University who sought to establish objective technology that could improve on the conventional Pap smear test.  They believed that it should be possible to distinguish between normal and abnormal tissue by measuring changes in physical properties, such as electrical impedance. 

  • 1999

    First gen ‘Opto Electrical’ Technology developed

    After an extensive and intensive R&D phase, between 1986 and 1999, the first generation TruScreen cervical cancer screening system was developed using the ‘Opto Electrical’ Technology for the detection of pre and cancerous cells on the cervix.

  • 2002

    First generation device launched by Polartechnics and CE Mark obtained.

  • 2014

    R&D begins on second generation device

    The R&D phase to develop the current second generation device commenced with a series of independent design houses in Feb 2014 and a pilot production version was available for the granting of the CE mark in 2016.

  • 2016

    Second gen TruScreen device launched

    In 2016, the second generation device “TruScreen Ultra” was launched. This built on TruScreen’s world-class medical technology with a number of improvements including significantly increased processing capacity, faster processing, and significantly improved performance. In addition, the handpiece is now wireless and the enhanced device offers wi-fi connectivity, extended battery life, and an LCD touchscreen.

  • 2018

    Large scale pilot programs in China with CDC and COGA commenced

    15,661 women were screened across 64 hospitals in 9 provinces over 3 years - TruScreen’s largest trial to date.

  • 2023

    China COGA study multi-province screening results exceed expectations

    Preliminary results released at the Annual Meeting of the American Society for Colposcopy and Cervical Pathology.

    Trial manuscript in review for publication in the Journal of the American Medical Association.

  • 2024

    TruScreen included in Chinese Obstetricians and Gynaecologists Association (COGA) Blue Book and Chinese Society For Colposcopy and Cervical Pathology guidelines

  • 2024

    TruScreen acknowledged in Unitaid Technology Landscape Report

    Unitaid brought TruScreen’s AI-based opto-electrical device to the attention of the global cancer screening community in a joint publication with the World Health Organisation and Clinton Health Access Initiative.

    Read the Technology Landscape Report: “Screening and treatment of precancerous lesions for secondary prevention of cervical cancer.”

Truscreen cervical cancer screening device

Intellectual Property

TruScreen holds trade marks and patents that afford the Company proprietary protections in respect of its intellectual property rights that it has developed.

Additional research and development is also planned to improve the manufacturing processes to reduce the cost of manufacture of the products to improve gross margins. TruScreen is committed to ongoing product innovation and is consistently conducting research and development projects to ensure the device remains best in breed.

The TruScreen Ultra Algorithm

TruScreen’s technology contains a sophisticated algorithm framework that has been developed in collaboration with the Australian Government’s applied research division, CSIRO. The algorithm was researched and developed from data sets collected from the Auckland Hospital, Royal Hospital for Women (Sydney), and The Whittington Hospital (London) between 1998 to 2000.

More than 23 man-years were spent on algorithm development and testing to arrive at the current version of the TruScreen Ultra classifier algorithm. During development, numerous algorithm methodologies were trialled.  The current TruScreen Ultra algorithm was selected following trials of 5 competing algorithms.

The current TruScreen Ultra algorithm is AI-enabled and uses a trained multidimensional probabilistic tissue features classification engine to provide a binary classification result (Normal or Abnormal) with a high degree of Sensitivity and Specificity.  The data sets used to train the algorithm consist of patient-specific clinical data combining clinical diagnosis information from colposcopy, cytology, and histology. The training data set consists of more than 7,500 multi-probing data sets, from patients of varying ethnicities with differing histological diagnoses.

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