Pumas-AI Launches Pumas Software to Advance Drug Development, Patient Care

July 23, 2019

BALTIMORE, July 23, 2019 — Pumas-AI, a new company established by University of Maryland School of Pharmacy faculty members Vijay Ivaturi, PhD, assistant professor in the Department of Pharmacy Practice and Science (PPS), and Joga Gobburu, PhD, MBA, professor in PPS – is proud to announce the release of its first cutting-edge software platform for pharmaceutical researchers and clinicians. Known as Pharmaceutical Modeling and Simulation (Pumas), the software was developed through a partnership with experts at Julia Computing. Research and software development efforts were led by Christopher Rackauckas, PhD, senior research analyst in PPS, with input from independent contributor Joakim Nyberg, PhD, from Uppsala, Sweden.

“The success rate for pharmaceutical innovations is approximately two percent,” says Gobburu, who also serves as executive director of the Center for Translational Medicine (CTM) at the School of Pharmacy. “Pumas software is tailored to revolutionize big data analytics in health care, unlike those tools used in other fields. By combining the extensive health care knowledge of our faculty and staff with the scientific computing experts at Julia Computing, we have developed a tool that will not only benefit business leaders working in the pharmaceutical industry, but also those who are caring for patients on the frontline of health care delivery.”

Pumas is the first software platform released by Pumas-AI, whose goal is to double pharmaceutical and patient care success rates by democratizing tools and education in the health care data analytics space. The Pumas software platform provides a wide range of analytic capabilities for pharmaceutical and biotechnology development, as well as therapeutic decision making – addressing a crucial need for pharmaceutical companies and investors, who often base their decisions on a combination of technical, regulatory, and commercial success probabilities, all of which the Pumas software can provide quantitatively.

“Pumas is our company’s first product specifically designed for professionals in the pharmaceutical and health delivery sectors to bridge this gap,” adds Gobburu. “It leverages the Julia programming language, and combines modern artificial intelligence (AI) with traditional mechanistic models, allowing the CTM to foster one of its goals of enhancing real-world data (RWD) analytics through its newly formed Health Analytics Collective (HAC).”

A comprehensive platform based on the Julia programming language, Pumas contains multiple modules designed to meet the needs of analysts in the pharmaceutical industry, while also working to advance therapeutic innovation in the clinic setting. Julia was selected for its speed and succinctness as a programming language, which produces an interface that looks similar to R, but operates at the speed of FORTRAN. Because Pumas is created entirely in Julia, users can make direct use of the language’s database, statistics, and visualization functionality – all without losing performance.

In addition, Julia is the programming language of choice for prominent researchers at institutions such as the Massachusetts Institute of Technology (MIT) who work on projects at the cutting-edge of machine learning, as well as in differential equations research, which means that, unlike many other tools, Pumas has the unique ability to directly incorporate modern techniques to achieve maximal efficiency and accuracy.

“Pumas is the first pharmaceutical modeling suite that is designed from the ground up to use modern graphics processing unit (GPU) hardware, parallelized stiff differential equation solvers, and allow for the integration of machine learning with pharmacometrics,” says Rackauckas. “We are excited to not only accelerate current workflows, but also help users explore the new, realistic models that are enabled by this technology.”

Pumas will be the topic of a workshop at JuliaCon 2019, the year’s biggest Julia conference for developers, enthusiasts, and others. JuliaCon will be held at the University of Maryland, Baltimore in Baltimore, Md., from July 23 to 26, 2019, including a full day of preconference workshops scheduled for July 22.

A preconference workshop hosted by the CTM that day will highlight the Pumas software platform.

“At the CTM, we strive to develop point-of-care solutions for providers and clinicians that can help individualize treatment for patients,” says Ivaturi, who also serves as a pharmacometrician in the CTM at the School. “The Pumas software platform will be instrumental in helping us optimize treatments for a number of conditions and therapeutics.”

He adds, “It is going to revolutionize therapeutic decision making and allow health care organizations to benefit from payor incentives by demonstrating substantial improvements to successful patient care.”

Researchers and clinicians can learn more about Pumas at www.pumas.ai.

About Pumas-AI

Pumas-AI was established by University of Maryland School of Pharmacy faculty members: Vijay Ivaturi, PhD, assistant professor in PPS, and Joga Gobburu, PhD, MBA, professor in PPS and executive director of the Center for Translational Medicine at the School. Pumas-AI’s vision is to double pharmaceutical and patient care success by democratizing tools and education in the health care data analytics space. Pumas is its first product developed to provide analytic capabilities for drug/biotech development and therapeutic decision making.  It leverages the power of the Julia programming language to combine modern AI with traditional mechanistic models to gain massive computational efficiency.

About Center for Translational Medicine

Established in 2011, the Center for Translational Medicine (CTM) analyzes and summarizes data from experiments and clinical trials using quantitative disease, drug, and trial models, with the goal of reducing the time it takes to bring a drug to market. Its quantitative models, along with state-of-the-art development techniques – such as adaptive and enrichment trials – are integrated into tools that drug developers, regulatory agencies, and other research organizations can use to guide decisions pertaining to “go/no-go”, dosage, patient population, design, endpoint, analyses, and therapeutics choices.

About the University of Maryland School of Pharmacy

Established in 1841, the University of Maryland School of Pharmacy is ranked as one of the top 10 schools of pharmacy in the United States. It is a thriving center for professional and graduate education, pharmaceutical care, research, and community service. It creates the future of pharmacy by pioneering new roles for pharmacists in advanced clinical practice and conducting cutting-edge research in drug discovery and development, comparative effectiveness and patient-centered outcomes, and disease management. Faculty inspire excellence in more than 800 students, residents, and postdoctoral fellows through a contemporary curriculum, innovative educational experiences, and strategic professional relationships.

About Julia Computing

Julia Computing was founded by the creators of Julia. Julia is an open-source language for high-performance scientific computing, data science, and AI developed by a community that consists of some of the best people in these fields. It solves the long standing two-language problem by combining the simplicity and ease of use of dynamic languages such as Python and R with the performance of statically typed languages such as C++ – for which its creators were awarded the 2019 James H. Wilkinson Prize for Numerical Software. Julia is now taught and used for research at hundreds of universities worldwide, including MIT, Stanford, UC Berkeley and Cornell to name a few. Julia Computing’s mission is to develop products that make Julia easy to use, easy to deploy and easy to scale. It does so through a suite of products – JuliaSure, JuliaTeam and JuliaPro, which are used by hundreds of enterprises and universities worldwide. For new users of Julia, live and online trainings are offered through JuliaAcademy.

About Health Analytics Collective

The Health Analytics Collective is a group founded by the CTM, MIT, Julia Computing, and MMS Holdings that plans to use Pumas as part of an end-to-end solution for data science and real world evidence analytics, allowing for the ingestion, transformation, and analysis of all data in one system. The group aims to leverage real-world evidence, observational data that are generated during routine clinical practice, and patient health care databases to augment label claims and/or support new drug applications with leading-edge software and algorithms and a depth of regulatory and clinical experience.


Source: Julia Computing 

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire