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AI in regulated medical solutions: overcoming the risk, embracing the benefit

21 March, 2023

AI has become a much more common element of medical devices in the past few years, with submissions increasing rapidly over the last 3 years. This significant growth is being…

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Artificial Intelligence, an Ally for Health

13 March, 2023

If we asked the most famous artificial intelligence (AI) based chat today about the role that data analysis plays in everyday clinical practice, it would respond that it is increasingly…

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Nutraceutical & functional food research & development webinar

21 February, 2023

NutriGuard is a machine learning framework designed and developed by Topazium to harness the potential of food components for promoting and preserving health. It is inspired by the need to understand…

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Finding a needle in a haystack: virtual screening, an artificial intelligence approach to drug discovery

2 February, 2023

Artificial intelligence (AI) is a technology well suited for dealing with large amounts of information and has long been considered a promising tool in drug discovery. It has made steady…

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A machine learning (ML) approach for identifying genetic biomarkers and new molecular targets associated with impaired survival of breast cancer patients

18 November, 2022

BACKGROUND Machine learning (ML) tools are suitable to dive vast amounts of clinical and genetic information in order to identify genetic biomarkers of worse survival and potential new molecular targets.…

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Prospective evaluation of SkinGuard, a deep algorithmic framework for the classification of neoplastic skin lesions

10 November, 2022

Introduction. Diagnostic errors between nevic lesions and skin tumors are frequent for non-specialist physicians. Therefore, there is a need to create a simple and practical tool based on artificial intelligence…

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Harnessing the power of AI and HTE, cloud lab and automation data to transform drug discovery

8 November, 2022

Drug discovery is a lengthy and costly process affected by a high attrition rate. The revolution in experimental sciences brought about by HTE, cloud labs and lab automation should represent…

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El arte de la medicina hipocrática y la IA: un binomio al servicio del paciente

6 October, 2022

En un mundo en constante cambio y evolución como el nuestro, pocos métodos o doctrinas pueden tener el honor de permanecer vigentes durante más de 2.000 años. Uno de estos…

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Globant and Topazium Announce Partnership to Deliver AI-Powered End-to-End Solutions to the Life Sciences Industry

28 September, 2022

Globant and Topazium join to create new paradigms in drug discovery, clinical research, diagnostics, and well-being MADRID – September 27, 2022 – Globant (NYSE: GLOB), a digitally native company focused…

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A deep learning framework (DLF) to identify clinical predictors of disease progression and mortality in metastatic castration-resistant prostate cancer (mCRPC) patients treated with docetaxel/prednisone (DP)

5 June, 2022

Background: Treatment with DP improves survival in mCRCP but is associated with significant toxicity. The question remains as to whether the improved survival is worth the toxicity risk. In this…

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Profiling of clinically relevant subgroups of asymptomatic or mild-symptomatic metastatic castration-resistant prostate cancer (mCRPC) patients using PSA and testosterone levels and deep learning

4 June, 2022

Background: The optimal time to begin therapy in mCRPC patients who have either no, or minimal symptoms is not defined yet. Estimating prognosis of these patients can avoid undertreatment or…

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Development and validation of a predictive score to identify K-Ras wild-type (WT) metastatic colorectal cancer (mCRC) patients who are likely to benefit from Panitumumab (P) treatment

3 June, 2022

Background: Practice guidelines recommend using P to treat K-Ras WT mCRC patients where it was shown to significantly extend overall survival (OS). Still, a proportion of patients will not achieve…

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Analysis of transcriptomic responses to SARS-CoV-2 reveals plausible defective pathways responsible for increased susceptibility to infection and complications and helps to develop fast-track repositioning of drugs against COVID-19

1 June, 2022

Background: To understand the transcriptomic response to SARS-CoV-2 infection, is of the utmost importance to design diagnostic tools predicting the severity of the infection. Methods: We have performed a deep…

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Visit our booth at SLAS Europe 2022!

25 May, 2022

Visit our booth at SLAS Europe 2022 and see how our AI systems can improve your drug discovery programs!

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TOPAZIUM selected for the SLAS 2022 Innovative AveNEW lineup!

3 May, 2022

Topazium has been selected for the final Innovative AveNEW lineup at #SLASEurope22 in Dublin. Very honored for this recognition and eager to share out latest advances in such a renowned forum within…

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TOPAZIUM is selected for the StartupsMeetHealthcareProviders program

27 April, 2022

We are very proud to announce that we are one of the seven companies selected in the Start-ups Meet Healthcare Providers program. The programme matches the start-ups behind the innovative…

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TOPAZIUM receives the “INNOVATIVE SME” label!

24 February, 2022

We have been labeled as “Innovative SME” from the Ministry of Science and Innovation.

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Ageing and Carcinogenesis

12 February, 2022

Despite their wide differences (1), most theories about cancer proposed during the past century agree that cancer is a biological nonsense for the organism in which it originates since cancer…

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Would you like to be part of a team that works every day to create a wiser medicine?

26 January, 2022

CAREERS Open positions. We are expanding our team in Madrid. If you’re looking for a new challenge which will fulfil and inspire you, join us:   SENIOR ARTIFICIAL INTELLIGENCE MANAGER…

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TOPAZIUM receives NEOTEC GRANT!

20 January, 2022

We are very proud to share that we have been awarded by the Centre for the Development of Industrial Technology (CDTI) with a NEOTEC 2021 grant. This public support will…

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Detecting panitumumab/FOLFOX responders in K-Ras wild-type metastatic colorectal cancer through an artificial intelligence-based analytical tool

30 June, 2021

Background: Patients with K-RAS wild-type (WT) metastatic colorectal cancer (mCRC) are currently considered the optimal candidates for upfront treatment with combinations of chemotherapy and EGFR inhibitors. These combinations significantly extend…

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Use of deep learning frameworks to detect super-responder and super-survivor stage IV squamous non-small-cell lung cancer (NSCLC) patients treated with a gemcitabine and cisplatin combination

23 May, 2021

Background: Synthetic fingerprints integrate clinical data within computational models allowing the identification of particular clinical subpopulations at a given moment. We here describe a deep learning strategy to detect super-responder…

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Predicting disease progression and mortality in metastatic colorectal cancer patients (mCRC) through an artificial intelligence-based analytical tool

23 May, 2021

Background: Predicting the clinical course of metastatic disease remains a key challenge in CRC. Estimating prognosis of these late-stage patients can avoid undertreatment or overtreatment and also guide the follow-up…

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Deep Neural Frameworks Improve the Accuracy of General Practitioners in the Classification of Pigmented Skin Lesions

3 December, 2020

This study evaluated whether deep learning frameworks trained in large datasets can help non-dermatologist physicians improve their accuracy in categorizing the seven most common pigmented skin lesions. Open-source skin images…

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Why we do what we do. A brief analysis of cancer therapies

6 November, 2020

The goal of all medical activity is to preserve health in fit people, and to restore the sick into a state of complete physical, mental and social wellbeing. In an…

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Artificial intelligence: a disruptive tool for a smarter medicine

20 August, 2020

Although highly successful, the medical R&D model is failing at improving people’s health due to a series of flaws and defects inherent to the model itself. A new collective intelligence,…

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Covid-19: la inteligencia artificial al servicio de la medicina

1 July, 2020

A medida que se acelera y agrava la situación sanitaria de Covid-19, es inminente la utilización de tecnologías que permitan no sólo frenar la propagación del virus sino también detectarlo…

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Lessons from Hippocrates: time to change the cancer paradigm

8 June, 2020

The ultimate goal of all medical activity is to restore patients to a state of complete physical, mental, and social wellbeing. In cancer, it is assumed that this can only…

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Robust COVID-19-related condition classification network

27 May, 2020

COVID-19 can exponentially precipitate life-threatening emergencies as witnessed during the recent spreading of a novel coronavirus infection which can rapidly evolve into lung collapse and respiratory distress (among other various…

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Deep neural frameworks improve the accuracy of general practitioners in the classification of pigmented skin lesions

15 May, 2020

Artificial intelligence can be a key tool in the context of assisting in the diagnosis of dermatological conditions, particularly when performed by general practitioners with limited or no access to…

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Topazium joins the largest telemedicine network in Latin America

6 May, 2020

A new partner in the largest telemedicine network in Latin America: Topazium Artificial Intelligence and Telmed shares the same vision: uniting against COVID-19 by providing a high-quality, collaborative and technological…

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Augmented Dermatology: Pioneer of Artificial Intelligence in Healthcare

2 March, 2020

Skin lesions are one of the most common human diseases and affect millions of people worldwide 1. Moreover, its prevalence will raise every year due to the aging of the…

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Smarter Medical Research Through a New Collective Intelligence

1 October, 2019

Around 200 billion US dollars are invested every year in medical research worldwide (1). The result of this collective effort has been astonishing: In just 100 years, life expectancy rocketed…

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From Hippocrates to Artificial Intelligence

18 July, 2019

Moving Towards a Collective Intelligence “The physician should convert or insert wisdom into medicine and medicine to wisdom.” (Hippocrates, physician, 460 BC – 370 BC). Modern medicine is based upon…

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X-rays | Covid-19

COVID-19 detector: Our tool uses a deep convolutional network to detect and locate radiological signs associated with COVID-19 in frontal chest radiographs, differentiating them from those associated with common bacterial and viral pneumonias. The physician supplies the anonymized radiological image via a cell phone, website, or email to the cloud. The system also generates a heatmap indicating the region of the image where the algorithm detects radiological signs associated with this pathology.

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Mammogram

Mammogram Analyzer: Mammograms can be difficult to interpret as the precision of the procedure depends in part on the technique used and the experience and skills of the radiologist. Topazium has designed and implemented a tailor-designed deep convolutional network on the task of detection and localization of abnormal radiological signs on mammograms. Our AI-based assistance tool could improve the overall accuracy of mammography reading and reducing the radiologists’ workload. It would also help in releasing the results of mammograms on patients’ schedules rather than those of radiology departments.

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X-rays | Pneumothorax

Pneumothorax localizer: Clinical suspicion of pneumothorax is usually confirmed by a radiologist based on a chest X-ray, a procedure which could be challenging if performed by professionals without extensive training. Topazium has implemented a framework that can detect and localize a pneumothorax in a given chest X-ray unsupervisely.

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X-rays | Global Analyzer

Global Analyzer: Chest radiography is one of the most commonly performed diagnostic examination for cardiovascular and respiratory life-threatening diseases. Engineered on the basis of deep neural networks, Topazium implemented a platform which detect and localize the presence of 16 radiological signs indicative of cardiovascular or respiratory clinical conditions on a frontal chest radiography faster than current clinical practice. The system can reduce time to diagnosis as well as fatigue-based diagnostic errors. It can also increase access to medical imaging expertise in parts of the world where interaction with skilled radiologists is limited.

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X-rays | Tuberculosis

Tuberculosis detector: Although chest X-rays provide important clues to tuberculosis early diagnosis, there are no radiological features which are in themselves pathognomonic of the infection, adding an additional difficulty for non-trained practitioners on detecting the disease. Topazium’s system could aid radiologists or other health care staff reading radiographic films, in tuberculosis systematic screening, infection control, and reduction of the cost of case detection within triage algorithms.

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Cancer

Patient-Drug Mapper: A significant number of hi-potential drugs end up falling through the cracks given their testing on patients with incompatible individual profiles. Topazium’s analytics allow the mapping of genetic and clinical patient’s conditions to a whole universe of experimental and approved drugs. Also, it can be used to produce a rank of matching alternative drugs given a patient’s profile, aiming both to increasing treatment efficiency whilst allowing drug re-profiling of vintage failed projects.

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Radiology

Pediatric Bone-Age Estimator: Calculating bone age through traditional procedures based on left wrist, hand, and fingers X-rays could be time-consuming and cumbersome. Topazium’s solution to this challenge is an algorithmic framework which instantly estimates the subject’s age by processing the aforementioned X-ray. Topazium’s system assess skeletal maturity with a mean absolute error of around 4 months, which is below the figure observed among practitioners.

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Retinopathies

Diabetic retinopathy (DR) can affect anyone with hyperglycemia, though it primarily impacts people who have had diabetes for many years. It can cause permanent blindness if left undiagnosed and untreated. Clinicians can identify DR by ophthalmoscopy or retinopathy. While these approaches are effective, they require a high degree of expertise. Topazium has developed a framework that can automatically classify ocular fundus images according to the various severity degrees of DR.

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Phatology

Lymph Node Metastasis Detector: Defining the presence or absence of lymph node metastases is essential in cancer diagnostics and staging, as it affects treatment and prognosis. This task is highly relevant but requires large amounts of reading time from a pathologist on-site or close to the point-of-care to analyze the samples. TOPAZIUM’s framework can detect cancer metastases in lymph nodes with an accuracy similar to the efficiency reported in the literature by expert pathologists.

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Dermatology

Pigmented-Skin Lesions Classifier: Diagnosis in dermatology is largely based on visual inspection of a lesion or the suspicious skin area, depending largely on the experience and training of the dermatologist (or, general practitioners in areas where dermatological services are not readily available). Topazium’s framework currently classifies nine common pigmented-skin lesions with an accuracy similar to the efficiency reported in the literature by well-trained dermatologists.

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Radiology

Pneumothorax Diagnostician: Clinical suspicion of pneumothorax is usually confirmed by a radiologist based on a chest X-ray, a procedure which could be challenging if performed by professionals without extensive training. Topazium has implemented a framework that can detect and localize a pneumothorax in a given chest X-ray unsupervisely.

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Dermatology

Melanoma: Diagnosis in dermatology is largely based on visual inspection of a lesion or the suspicious skin area, depending largely on the experience and training of the dermatologist (or, general practitioners in areas where dermatological services are not readily available). Topazium’s framework currently classifies seven common pigmented-skin lesions with an accuracy similar to the efficiency reported in the literature by well-trained dermatologists.

Privacy policy

TOPAZIUM WEB DATA PROTECTION POLICY

 

Who is the Data Controller?

The controller of your personal data is TOPAZIUM with registered office in Paseo de la Castellana 40, 8th floor, 28046, Madrid, Spain.

For any queries or requests you have about data protection, you can contact TOPAZIUM at the following email address: info@topazium.com

 

What are the purposes of processing personal data?

  1. A) Contact mail:

In the event that you have filled in your details in the “Contact Us” section, TOPAZIUM will process your personal data in order to respond to and manage your contact request by resolving the request for information you may have required.

TOPAZIUM will only process the personal data that you provide together with the message sent through the form.

The processing of this personal data by TOPAZIUM to resolve your query is based on the interest of TOPAZIUM to offer the best possible service to any third party interested in the activity of TOPAZIUM.

  1. B) Cookies:

The TOPAZIUM website installs cookies on users’ browsing devices in order to ensure the proper functioning of the website and to analyze the behavior of users. The installation of cookies is carried out voluntarily by Users who can withdraw their consent at any time by configuring cookies through the control panel provided by TOPAZIUM. You can find more information about cookies in our Cookies Policy.

 

How long will we keep your data?

We will process your data for as long as necessary to respond to and resolve the request you have made to us through the Contact Us section.

In the case of cookies, the data may be processed as long as you maintain your consent for its installation and for the duration of the installation of the same.

To whom do we communicate your data?

TOPAZIUM has collaborators who to provide their services can access the personal data of TOPAZIUM.

TOPAZIUM makes a careful selection and control of these third parties with which it has signed data protection agreements, where they are obliged to comply with a number of data protection obligations.

TOPAZIUM may also communicate data of interested parties to the administrative authorities that require it.

 

What are the rights of your personal data and how to exercise it?

You may, in the terms established in the data protection regulations, revoke at any time the authorization granted for the processing and transfer of your personal data, as well as exercise your rights of access, rectification, opposition, limitation, deletion, portability and not be subject to automated decisions, writing to TOPAZIUM to the email address info@topazium.com or to the address Paseo de la Castellana 40, 8th floor, 28046 Madrid, Spain.

 

How can you enforce your data protection rights?

If you believe that any of your data protection rights have been violated, you may contact TOPAZIUM to rectify or end your concern about the matter at the address mentioned in the previous section. In any case, you can always contact the data protection authorities to safeguard your rights www.aepd.es

Laboratory test

Biological Age Predictor: Topazium has designed and implemented a framework to accurately estimate a subject’s biological age from routine laboratory tests’ outputs. Additionally, it identifies the key metrics responsible for the potential basis between biological and chronological age, allowing professionals to prescribe rectifying actions aiming to close the referred biological/chronological age gap.