Certara, Silo Pharma advance AI strategies with Nvidia initiatives

1 min read     Updated on 08 Jul 2026, 02:22 AM
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Jubin VScanX News Team
AI Summary

Certara Inc. and Silo Pharma Inc. are advancing their AI strategies through separate collaborations with Nvidia Corp. Certara is integrating Nvidia’s BioNeMo Agent Toolkit into its drug development platform to enable autonomous life sciences research. Silo Pharma’s subsidiary, QwikAgents, has joined the Nvidia Developer Program to access AI software ecosystems and accelerate platform enhancements. These initiatives aim to streamline complex workflows and support scalable AI-driven operations in the life sciences sector.

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Nvidia Corp. expanded its presence in life sciences AI through separate initiatives with Certara Inc. and Silo Pharma Inc. Certara is integrating Nvidia’s BioNeMo Agent Toolkit into its AI-driven drug development platform, while Silo Pharma’s subsidiary, QwikAgents, has joined the Nvidia Developer Program to strengthen its AI agent capabilities.

Certara Integrates Nvidia BioNeMo Into AI Drug Development Platform

Certara is partnering with Nvidia to advance its open, integrated AI platform by combining its scientific software, regulatory expertise, and proprietary datasets with AI-first, agentic frameworks. Under the collaboration, the Nvidia BioNeMo Agent Toolkit will become one of several agentic frameworks available within Certara’s platform. The toolkit is designed to turn AI agents into autonomous life sciences researchers by providing access to Nvidia’s life sciences technology stack while complementing Certara’s biosimulation models, regulatory expertise, and scientific teams.

AI Agents Target Drug Development Workflows

Specialized AI agents will analyze scientific models, datasets, and domain expertise across multiple stages of drug development. These agents can support tasks such as optimizing dosing strategies using systems pharmacology models, analyzing clinical datasets, simulating patient and clinical trial scenarios, evaluating ADMET properties, assembling regulatory-ready evidence, and assessing early-stage drug discovery hypotheses. The technology is intended to enhance the work of biosimulation experts and scientific teams by accelerating insight generation while keeping scientists at the center of decision-making.

Silo Pharma Subsidiary Joins Nvidia Developer Program

Silo Pharma announced its wholly owned subsidiary, QwikAgents, has joined the Nvidia Developer Program. QwikAgents’ platform automates complex workflows using autonomous AI agents capable of reasoning, taking action, and interacting with enterprise systems. The platform also incorporates persistent memory, intelligent routing across multiple large language model providers, browser automation, and secure data management to support scalable AI-driven operations. Participation in the Nvidia Developer Program will provide QwikAgents with access to Nvidia’s AI software ecosystem, development frameworks, technical training, and optimization resources. Silo Pharma expects these resources to help accelerate platform enhancements as it expands AI agent capabilities for enterprise customers.

Company Stock Price Change
Certara Inc. $7.09 -0.63%
Silo Pharma Inc. $6.09 -2.10%

How will the integration of Nvidia's BioNeMo Agent Toolkit impact Certara's competitive positioning against other AI-driven drug discovery platforms?

What specific metrics or timelines should investors watch to gauge the success of Silo Pharma's QwikAgents platform enhancements through the Nvidia Developer Program?

Could these partnerships signal a broader trend of Nvidia shifting focus from hardware provision to specialized AI software ecosystems in the life sciences sector?

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Nvidia shares fall on report DeepSeek is developing AI chips

1 min read     Updated on 07 Jul 2026, 07:51 PM
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Reviewed by
Naman SScanX News Team
AI Summary

Nvidia Corporation shares declined following reports that China's DeepSeek is developing its own artificial intelligence chips for inference. The initiative, started about a year ago, aims to reduce DeepSeek's reliance on Nvidia and Huawei chips. Nvidia stock was trading 1.62% lower at $192.39.

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Nvidia Corporation shares are trading lower following reports suggesting China’s DeepSeek is developing AI chips for inference, which reduces its reliance on the company. The potential shift in strategy by a major AI player poses a risk to Nvidia's dominance in the semiconductor market, as inference chips are critical for running trained models. Nvidia stock was down 1.62% at $192.39 at the time of publication.

DeepSeek’s Quiet Push Into Semiconductors

According to Reuters, DeepSeek is developing its own AI chip designed for inference — the stage of AI computing in which a trained model generates responses for users — rather than for training new models. The effort began approximately a year ago and remains at an early stage, with DeepSeek reaching out to external chip-design, foundry and memory companies. The company has also quietly increased hiring of chip-design engineers in recent months without posting public job listings.

If successful, the move would mark a major strategic shift for DeepSeek — widely regarded as China’s AI champion — and could reduce its reliance on both Nvidia and Huawei chips, which it has historically depended on to train and run its globally popular models.

The Broader Context

DeepSeek would be joining a growing list of AI companies seeking to reduce dependence on Nvidia by developing custom silicon. OpenAI last month unveiled Jalapeño, its first custom inference chip developed with Broadcom, while Anthropic has been weighing building its own chips, Reuters reported in April.

Metric Value
Stock Price Change -1.62%
Current Price $192.39

How will Nvidia adjust its pricing strategy for inference chips if more major AI developers successfully transition to custom silicon?

Could DeepSeek's move accelerate similar in-house chip development efforts among other Chinese AI firms facing US export controls?

What is the projected timeline for DeepSeek to mass-produce these chips, and how might delays impact its current operational costs?

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