Tempus uses data to aid the personalized cancer treatment. The software helps doctors to know a patient’s body system and understand what influence it might have on disease progression and therapy treatments.
As cancer cases become more complex, one medicine for all patients is proving ineffective. Tempus helps doctors assess risks, pick the right treatments, and measure potential outcomes by examining clinical records, molecular profiling, and advanced analytics at the same time.
Cancer is not a single disease. Even for a group of people with the same cancer type, their tumors are different at the molecular level. For example, two patients with ovarian cancer may share one diagnosis, but they will have completely different genetic profiles influencing how fast the disease develops and how it responds to therapy.
That is why people die from certain types of cancer that others have survived. Personalized cancer treatment comes into the mainstream as a response to this question. Personalized treatments encourage oncologists to ask, “What works for this patient?”, and not, “Will what worked for this patient work for the next?” Tempus rose up to this challenge by designing a data system able to connect molecular insights with real-world clinical outcomes.
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In the evolving world of oncology, doctors are constantly looking at data and machine learning to understand the complex nature of cancer in an easy way. Founded in 2015 by Eric Lefkofsky, Tempus is a health technology company that is a leading example of this shift. Tempus uses data from extensive research, advanced analytics, and AI tools to support precision oncology. This method provides medical care based on an individual’s physiological system rather than drawing from a large pool of similar cancer cases.
Tempus’ mission is clear: to create a healthcare data platform that enables the use of precision oncology. The company doesn’t function on its own as a laboratory or diagnostic provider. Instead, it is in partnership with doctors, researchers, and medical companies, hoping to improve treatment for cancer care. Some of Tempus’s methods include the following:
Tempus’s provides analytical procedures that are able to put tumor DNA and RNA in order, including solid tumor profiling, liquid biopsy analyses, and broader panels that can capture germline and somatic variants. These tests provide detailed information that can be of help to medical practitioners. Used to determine the right therapy for a cancer patient.
Tempus uses an AI-enabled care intelligence platform, “Tempus Next.” It is designed to provide credible information from the patient’s record. Using data from electronic health records (EHRs), laboratory results, imaging, and pathology, this AI helps doctors to see where the problem lies and flags patients that might benefit from a certain test under strict guidelines.
Data collection is a vital part of ensuring precision oncology. And there are several types of data to be collected in cancer care, including:
Clinical data are structured and unstructured data from a patient’s care journey. This usually includes diagnosis codes, treatment history, and lab results. Pathology reports, physician notes, and outcomes based on response to therapy or progress reports. Hospitals, clinics, and health institutions also contribute clinical records to add to Tempus’s growing database.
Tempus goes beyond traditional clinical records to perform next-generation sequencing (NGS) to get molecular data from tumor tissue and liquid biopsies. These analytical procedures also identify genetic mutations. Gene expression levels and other relevant biological features of the cancer in a patient.
Tempus keeps track of the data collected from patients who were treated outside of clinical trials. It also records how they respond to therapies and the effects of side effects as well.
Collecting data is only the first part of the process. These learning models are adapted to detect patterns that researchers or physicians might miss.
For example, Tempus can carry out tests on thousands of patient records in its system to find matches between a certain genetic problem and its treatment. As time goes on, it becomes insight for treatment recommendations, clinical trial matching, and research hypotheses.
Oncologists typically deal with a vast amount of patient data, which can be hard to monitor. Tempus helps doctors to sort through the pile of files by integrating data and AI into their workflows, ensuring that patient care is more informed and accurate.
For easy access, Tempus Hub can be viewed with a laptop or a mobile device, and it can also be integrated with electronic health records, allowing doctors to work in a familiar environment.
By integrating data, AI, and clinical context, Tempus assists doctors in three ways:
Working together, these factors help to reduce the burden on doctors and keep them focused on the parts of their jobs that require strategic decision-making processes, such as ensuring that treatment is aligned with each patient’s disease profile.
In a particular case, a woman with advanced-stage ovarian cancer had a cell-free DNA analysis. The results showed that she had inherited a particular, harmful gene that weakened its ability to repair damaged DNA. It was impossible to get this result through standard diagnostics. But based on this finding, she was prescribed a series of therapies that helped repair damaged DNA. After treatment, the disease was controlled beyond expectations.
Another case had a patient with a rare adenoid cystic carcinoma. Using that data obtained with Tempus, doctors were able to pick the right form of therapy, and the disease was stabilized. These treatments were not experimental lab decisions. They were real-life evidence showing that data gotten with Tempus can provide multiple treatment options when standard medical guidelines can’t.
Tempus points out just how much oncology is moving towards evidence-based personalization for efficiency in areas of research, treatment, and development.
Several trends are becoming clear:
As these trends continue to grow, personalized cancer treatment might potentially become the standard for cancer care.
Concluding, Tempus exists to make cancer care easier because of how complex and personal cancer is. By creating a healthcare data platform that is able to link clinical records, insights, and real-world outcomes simultaneously, Tempus helps doctors in picking the right treatment for each individual. Personalized cancer treatment also relies on high-quality clinical data, analytics, and responsible use of AI. The more oncology evolves, healthcare platforms like Tempus will be able to lead cancer treatment into a future where cancer care is more detailed, informed, and accurately aligned with an individual’s body.