SOPHiA DDM™ Multimodal Analytics Solutions

Unlocking predictive insights from multimodal digital health data to advance precision medicine

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With you in every step of the clinical 
research and development journey

Transforming multimodal data into powerful predictive insights with decentralized analytics and a global healthcare network. Expert guidance coupled with the machine learning-powered capabilities of the SOPHiA DDM™ Platform  enables you to explore unmet medical needs, pinpoint the super-responders and hard-to-treat patients in your clinical studies, streamline trial design and management, and optimize your investments. Don’t let fragmented and unstructured data hinder your clinical research and development programs.

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Moving toward powerful insights from unstructured data

The value of

Multimodal Analytics Solutions

Leverage our advanced analytical capabilities to get more from multimodal digital health data.

Eliminate time wasted on data standardization. Focus on what matters most.

Save valuable time and resources by letting our team of experts handle the standardization and computation of multiple types of digital health data independently of their source.

Reduce the uncertainty. Make decisions based on real-world evidence.

Go beyond genomics into a more comprehensive and longitudinal view of patient data. Uncover new signatures to apply at any stage of the clinical journey, from discovery to commercialization.

Maximize effectiveness by prioritizing real-world unmet medical needs.

Align your clinical research and development programs with the specific needs of your target patients to prioritize spending in critical areas and accelerate precision medicine rollout and adoption.

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Real-time, real-world, real insights

Draw insights from real-world and multimodal data to understand 
treatment responses and population outcomes.

Explore DEEP-Lung-IV

Explore multimodal data from our multi-centric and multimodal study on stage IV NSCLC (NCT04994795)

Co-develop new studies

Generate new multimodal data by co-developing new observational studies in any indication of your choosing

Join on-going studies

Save time by joining ongoing clinical studies on NSCLC, Glioblastoma, and others, with new data types, treatments, or experimental arms

Leverage multimodal signatures and the SOPHiA DDM™ RWD database to guide the development and training of models and algorithms.

Build algorithms & models

Launch and execute clinical research studies to inform the development of new algorithms

Train & validate with RWD

Leverage existing RWD to support the training and validation of your multimodal algorithms

Harness multimodal algorithms and predictive insights to improve trial efficiency, accelerating the development of effective precision therapies and improving return on investment.

Pinpoint super-responders and hard-to-treat patients

Investigate multimodal signatures associated with patients demonstrating exceptional responses to your precision therapies

Streamline clinical trial design

Identify prognostic and predictive biomarkers to guide the stratification of patient populations and optimize clinical trial design

Maximize trial efficiency

Gain real-time access to data to inform the creation of control arms and guide adaptive trial design efforts

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Exploring the power of Multimodal Analytics in cancer research

Lung Cancer
Brain Cancer
Breast Cancer
Kidney Cancer

Over the last 20 years, targeted compounds have been proven effective for non-small cell lung cancer (NSCLC patients). Recent scientific breakthrough has made immunotherapies a new pillar of cancer care.1

Yet, further research is needed to identify the patients most likely to benefit from these treatments.

In collaboration with academic partners, ongoing efforts aim to identify and test multimodal signatures to assess prognosis and predictive biomarkers in NSCLC patients treated with an immunotherapy regimen.

Learn more about our study in stage IIIA NSCLC:

Read the abstract → 

Learn more about our ongoing flagship study in stage IV NSCLC:

Clinical trials investigating meningioma therapies typically use the potentially restrictive endpoint of progression-free survival at 6 months (PFS6).

There is an urgent need to assess new treatment efficacy, considering tumor growth and characteristics.

In collaboration with academic partners, we investigated a statistical model demonstrating that 3D Volume Growth Rate (3DVGR) can complement PFS6 and provide a more comprehensive understanding of treatment response patterns.

Poly-chemotherapy is the standard treatment for early triple negative breast cancer (TNBC), typically administered prior to surgery to assess tumor sensitivity.2

Patients with residual disease after treatment have a higher risk of recurrence compared to those without. Differentiated follow-up treatment plans would benefit these patients, yet, more research is needed to establish robust prognosis biomarkers.

In collaboration with academic partners, we applied machine learning to baseline multimodal data to predict pathological complete response (pCR) status and identify patients who might benefit from additional treatments.

Locally advanced (pT3a) renal cell carcinoma (RCC) has a worse prognosis than pT1-T2.3 However, there are no practical tools that can assess individual risk of RCC upstaging to pT3a before the patient undergoes surgery. 

In collaboration with leading academic institutions, we developed a machine learning-based, contemporary, clinically relevant model to help surgeons estimate the risk of individual’s upstaging to pT3a, prior to surgery. 

One platform, multiple modalities

Discover the future of multimodal analytics with SOPHiA CarePath™. Be among the first to explore our upcoming application, built by healthcare data scientists to support clinical researchers and precision medicine developers in investigating longitudinal patient data at scale.

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Transforming Multimodal Analytics 
through key strategic collaborations


“By harnessing the power of advanced AI and machine learning models, we can integrate multiple forms of data to generate critical insights that can inform prognosis and response to therapy at the individual patient level. This approach aligns with our focus on developing personalised cancer treatments, which is currently driven by genomic-based biomarkers, and has the potential to elevate precision oncology into a truly multimodal, inter-connected health ecosystem.”

Greg Rossi

Senior Vice President, Oncology Europe & Canada, AstraZeneca

Our partnerships & collaborations

Click a link to read more about our partnerships & collaborations.

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Request a demo!

Get in touch to find out more.
Our client services team is on hand to answer any questions or schedule your live demo.


*Product in development – Technology and concepts in development. May not be available for sale.

SOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures, unless specified otherwise. The information on these webpages is about products that may or may not be available in different countries and, if applicable, may or may not have received approval or market clearance by a governmental regulatory body for different indications for use. Please contact [email protected] to obtain the appropriate product information for your country of residence.