PharmaMar looks to accelerate oncology research with AI through collaboration with Globant

Rhea-AI Summary

Globant (NYSE: GLOB) and PharmaMar announced a collaboration on March 19, 2026 to accelerate oncology R&D using a multi-agent AI framework.

The system delivers 15x faster insights, >90% accuracy, analyzes >4,500 documents and narrows >8,000 possibilities to 10 high-potential treatment-indication combinations.

Positive

• Insights 15x faster versus prior manual workflows
• Accuracy >90% in complex data retrieval
• Processes >4,500 research documents to prioritize candidates
• Reduces candidate set from >8,000 to 10 viable combinations

Negative

• None.

Key Figures

Insight speed gain: 15x faster Data retrieval accuracy: over 90% accuracy Digital agents: over 20 agents +3 more

6 metrics

Insight speed gain 15x faster Agentic AI system time-to-insights improvement

Data retrieval accuracy over 90% accuracy Complex data retrieval performance

Digital agents over 20 agents Specialized AI agents across preclinical, clinical, regulatory, commercial, strategy

Documents reviewed over 4,500 documents Research documents reviewed by system

Viable combinations 10 combinations Most viable treatment–indication combinations selected

Total possibilities over 8,000 possibilities Total treatment–indication combinations evaluated

Market Reality Check

Price: $45.04 Vol: Volume 857,680 is 0.51x t...

low vol

$45.04 Last Close

Volume Volume 857,680 is 0.51x the 20-day average of 1,693,061, indicating subdued pre-news trading. low

Technical Shares at $44.27 are trading below the 200-day MA of $67.98 and 68.88% under the 52-week high of $142.25.

Peers on Argus

Peers in Information Technology Services mostly showed declines (e.g., CNXC -5.5...

Peers in Information Technology Services mostly showed declines (e.g., CNXC -5.50%, VNET -3.56%, ASGN -2.37%, DXC -0.43%), suggesting sector pressure, but the AI oncology partnership appears stock-specific.

Previous Partnership,AI Reports

2 past events · Latest: Sep 30 (Positive)

Same Type Pattern 2 events

Date	Event	Sentiment	Move	Catalyst
Sep 30	AI partnership	Positive	-4.2%	Multi-year AWS collaboration to scale cloud and generative AI solutions.
Dec 11	AI partnership	Positive	-0.6%	Faros AI deal to optimize engineering workflows with agentic AI analytics.

Pattern Detected

AI partnership announcements have previously coincided with negative next-day moves, indicating a pattern of price divergence from seemingly positive collaboration news.

Recent Company History

Over recent months, Globant has combined steady financial disclosure with a series of AI-focused initiatives. Earnings for Q4 and full-year 2025 highlighted $2,454.9M in revenue, record free cash flow, and an AI-focused pipeline. Events like Globant Converge 2025 and multiple AI partnerships underscore a strategic emphasis on enterprise AI. However, prior partnership,AI headlines on Dec 11, 2024 and Sep 30, 2025 were followed by share price declines, suggesting investors have reacted cautiously to this theme.

Historical Comparison

-2.4% avg move · Past partnership,AI announcements saw an average move of -2.43%. This new PharmaMar collaboration ex...

partnership,AI

-2.4%

Average Historical Move partnership,AI

Past partnership,AI announcements saw an average move of -2.43%. This new PharmaMar collaboration extends Globant’s pattern of AI-focused alliances across industries.

Globant’s AI partnerships have evolved from internal engineering efficiency (Faros AI) to broad cloud and generative AI delivery (AWS) and now into oncology drug discovery with PharmaMar, showcasing diversification of its agentic AI use cases.

Market Pulse Summary

This announcement highlights Globant’s push to embed its enterprise AI capabilities in high-impact d...

Analysis

This announcement highlights Globant’s push to embed its enterprise AI capabilities in high-impact domains like oncology. The multi-agent system claims 15x faster insights and over 90% accuracy across more than 4,500 documents and 8,000 treatment–indication combinations. In context of prior AI partnerships and recent financial disclosures, investors may watch how such collaborations convert into revenue, margins, and expanded healthcare references over time.

Key Terms

agentic ai, regulatory, fda, ema

4 terms

agentic ai technical

"By leveraging agentic AI, we're building a new model for drug discovery..."

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.

regulatory regulatory

"analyzing large volumes of scientific, regulatory, and clinical data sources..."

Relating to rules, government agencies, and official approvals that control how companies operate, what products they can sell, and how transactions are reported. For investors, regulatory matters matter because they can change a business’s costs, legal risks, or ability to sell products — like a traffic light that can slow, stop, or clear the flow of a company’s growth and profits. Regulatory actions or changes can therefore affect stock value and investment risk.

fda regulatory

"global regulatory sources such as the FDA and EMA, allowing PharmaMar's teams..."

The FDA is the U.S. federal agency that evaluates and approves medical drugs, devices, biological therapies and certain foods; think of it as the gatekeeper that decides whether a medical product is safe and effective for patients. For investors, FDA decisions determine whether a company can sell a product, affect expected revenue and introduce regulatory risk, so approvals, rejections or safety warnings can quickly move a company's valuation and stock price.

ema regulatory

"global regulatory sources such as the FDA and EMA, allowing PharmaMar's teams..."

Exponential moving average (EMA) is a type of trend line that smooths a stream of recent price data while giving more weight to the newest prices, similar to how a spotlight focuses more on what's happening now than what happened long ago. Investors use EMAs to see whether a stock’s short-term direction is changing, to compare fast and slow averages for momentum signals, and to help time entries, exits, and risk controls without overreacting to random day-to-day noise.

AI-generated analysis. Not financial advice.

• The new alliance has launched a multi-agent AI framework to support faster, data-driven decisions in cancer research.
• Agentic AI system achieves 15x faster insights with over 90% accuracy.

MADRID, March 19, 2026 /PRNewswire/ -- Globant (NYSE: GLOB), a digitally native company that helps organizations thrive in a digital and AI-powered future, and PharmaMar, world leader in the discovery, development and commercialization of marine-derived anti-cancer drugs, today announced a new collaboration designed to speed up cancer drug discovery through artificial intelligence.

Through Globant Enterprise AI, the two organizations have created a multi-agent AI system that delivers more than 90% accuracy in complex data retrieval and reduces time to insights up to 15-fold, helping scientists select high-potential drug candidates for clinical development in a fraction of the time previously required.

The platform is capable of analyzing large volumes of scientific, regulatory, and clinical data sources to assist with decision-making across PharmaMar's R&D ecosystem and enable continuous, self-improving workflows.

Over 20 specialized digital agents are working across preclinical, clinical, regulatory, commercial and strategy areas, uniting human creativity and machine precision in the fight against cancer. Each agent collaborates within GEAI's secure architecture to process documents, simulate scenarios, and rank the most promising pharmaceutical assets.

The system enables reviews of over 4,500 research documents to prioritize the 10 most viable treatment-indication combinations out of over 8,000 possibilities  - work that would have taken months for human researchers to complete.

This intelligent system integrates information from internal databases, scientific publications, and global regulatory sources such as the FDA and EMA, allowing PharmaMar's teams to identify promising treatment combinations and make more informed, faster decisions.

"Drug discovery has always been a race against time, and in oncology, that time can mean everything," said Dr. Javier Jimenez, Chief Medical Officer at PharmaMar." By integrating Globant's AI technologies, we can process data from thousands of documents in seconds, simulate scenarios, and focus our research efforts where they have the highest potential to make a difference for patients."

Beyond speed and efficiency, the collaboration strengthens PharmaMar's ability to reuse institutional knowledge and fosters a new culture of digital innovation across its teams. In the next phase of the project, PharmaMar plans to extend these capabilities to enable hypothesis generation, real-time compliance checks, and automated content creation for scientific reporting.

"PharmaMar's vision proves what's possible when human intelligence and AI systems work side by side," said Ariel Capone, CEO of Globant's Healthcare and Life Sciences AI Studio. "By leveraging agentic AI, we're building a new model for drug discovery; one that brings precision and scalability to a field that directly impacts millions of lives."

About Globant

At Globant, we help organizations thrive in a digital and AI-powered future. Our industry-focused solutions combine technology and creativity to accelerate enterprise transformation and design experiences customers love. Through digital reinvention, our subscription-based AI Pods, and Globant Enterprise AI platform, we turn challenges into measurable business results and promised savings into real impact.

• We have more than 28,700 employees and are present in over 35 countries across 5 continents, working for companies like FIFA, Google, Riot Games, and Santander, among others.
• We were named a Worldwide Leader in Experience Design Services (2025), and previously recognized as a Worldwide Leader in AI Services (2023) by IDC MarketScape.
• We were featured as a business case study at Harvard, MIT, and Stanford.
• We are active members of The Green Software Foundation (GSF) and the Cybersecurity Tech Accord.
• We are global partners of Open AI, NVIDIA, AWS and Unity bringing world-class technology together to accelerate innovation across industries.

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SOURCE GLOBANT

FAQ

What did Globant and PharmaMar announce on March 19, 2026 about AI for oncology (GLOB)?

They launched a multi-agent AI framework to speed cancer drug discovery with rapid data-driven decisions. According to the companies, the platform delivers up to 15x faster insights and over 90% accuracy in complex data retrieval across R&D.

How much faster and how accurate is the new AI system from Globant and PharmaMar (GLOB)?

The system reportedly yields insights up to 15-fold faster and achieves >90% accuracy in data retrieval tasks. According to the companies, this accelerates selection of high-potential drug candidates across preclinical and clinical workflows.

How many documents and candidate combinations can the PharmaMar AI platform analyze (GLOB)?

The platform can review over 4,500 research documents and evaluate more than 8,000 treatment-indication possibilities. According to the companies, it prioritizes the 10 most viable combinations for further study.

Which data sources does the Globant-PharmaMar AI integrate to support PharmaMar's R&D (GLOB)?

The system integrates internal databases, scientific publications, and global regulatory sources including the FDA and EMA. According to the companies, this enables more informed, faster decisions across regulatory and clinical scenarios.

What next steps did PharmaMar announce for the AI collaboration with Globant (GLOB)?

PharmaMar plans to extend capabilities to hypothesis generation, real-time compliance checks, and automated scientific reporting. According to the companies, these next-phase features aim to broaden AI support across R&D workflows.