Pharmaceutical CMC
Consulting & Software

Rondaxe employs a diverse group of former directors and senior managers
from the pharmaceutical industry with expertise in chemical, fermentation,
drug product and analytical development and supply chain strategy.

 

Award Winning Software

When dealing with mountains of data the CentraDATA software can provide
context and structure, which is key to improving the challenging task of
bringing a drug to market.

 

TechTransfer

Tech or technology transfer is a mature discipline that follows a
structured approach with predictable outcomes. Each type of tech
transfer project presents its own set of unique risks. We make sure transfer
protocols are developed to capture the process thoroughly.

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Guiding You On The Drug Development Path To Success

Based out of New York, Rondaxe is one of the largest and most experienced international pharmaceutical development companies and CMC consulting groups in the world. We assist both virtual pharma/biotech companies and multi-national pharmaceutical clients from early development and formulation of pharmaceutical products through commercial manufacturing. Services include comprehensive CMC solutions, drug development, manufacturing and global regulatory strategies. [Re]source™ is our proprietary software that allows our clients to accurately and efficiently model Cost of Goods, perform should cost analysis, safely and accurately organize data for Tech Transfer and gives our users full transparency and traceability to simplify complex aforementioned tasks.

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CMC

Rondaxe CMC consulting group is focused on providing drug development and manufacturing strategies to the pharmaceutical industry.

EstiDATA

Complex pharmaceutical modeling – made easy.

TechTRANSFER

Streamlining and standardizing the Tech Transfer process.

Trusted By Some Of The Largest Pharmaceutical Organizations

Pharmaceutical companies across North America are benefiting from Rondaxe services

What our clients say

“AMPAC Fine Chemicals considers Rondaxe to be a ‘Key Skills Multiplier’ & have benefited from their support in critical strategic engineering and chemistry solutions. Additionally, their market knowledge & industry contact base prove to be of significant benefit to our business”

AMPAC

“Rondaxe Cost of Goods Software gives me a tool to quickly estimate manufacturing costs for intermediates and API, rigorously and reliably. The estimates are easy to understand and I can stand behind them when sharing with management or potential partners. Further, the output reports clearly highlight the key cost drivers and help my team focus their R&D efforts.”

Array BioPharma

Blog

Pharmaceutical IndustryRegulatory
September 19, 2024

Regulatory Landscape 2024

Recent trends in the regulatory landscape and healthcare could significantly impact the pharmaceutical industry. Expansion of Therapeutic Modalities: The modality landscape is broadening beyond traditional small molecules and proteins to include peptides, antibody-drug conjugates, nucleotide-based therapies (especially antisense oligonucleotides, siRNAs, and mRNAs), radionuclides (theranostics) and cell and gene therapies. This diversification brings new preclinical and drug development requirements and additional regulatory complexities.  For example, the complexities of bringing a radionuclide to market are amplified when regulatory agencies must cope with the fact that most radioactive therapeutics need to be used within one week – and often the same day – that they are manufactured.  These requirements necessitate regulation at the level of the radionuclide generator itself (68Ga and 99mTc) or as radionuclide precursor formulations (177Lu, 111In, 64Cu, 90Y) due to the sophisticated infrastructure involved. Increased Focus on Digital Technology: Regulatory changes in 2024 aim to clarify technology and data collection rules. This includes updates to the International Council for Harmonisation's…
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Data ManagementPharmaceutical IndustryResearch
August 13, 2024

AI in Pharmaceuticals: Embracing a Competitive Advantage 

The integration of generative AI in the pharmaceutical industry is revolutionizing drug development and manufacturing processes. This transformation is driven by the rapid advancements in AI technology, offering a competitive advantage to companies that adopt these innovations.  LLMs & AI Agents  Large Language Models (LLMs) such as GPT-4, are a type of AI that excels at understanding and generating natural language text. In pharmaceuticals, LLMs are useful for summarizing large amounts of scientific literature, generating hypotheses based on existing research, and facilitating communication between researchers and clinicians. They can also be used to create patient education materials and interpret complex medical data.  LLMs differ from AI agents in that agents have more autonomy. Agents are designed to automate tasks they are trained for, and don’t require as much human direction and input. Agents are designed for analyzing data, predicting outcomes, and optimizing processes. Some of their complex roles include drug discovery tasks, drug development and manufacturing optimization, and optimizing clinical…
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BusinessData ManagementPharmaceutical Development
June 7, 2024

Big Data Meets Big Pharma

Burgeoning Data The amount of data generated daily has grown exponentially in recent history. According to an article by Fabio Duarte, almost 329 million terabytes of data are generated each day, totaling 120 zettabytes annually (1 zettabyte = 1,000,000,000,000,000,000,000 bytes). Sensors on manufacturing equipment generate data based on current conditions and equipment performance. IoT devices can process this data to make immediate adjustments for optimal performance, quality, and regulatory compliance. Processing this “big data” efficiently can be a major source of competitive advantage for pharma companies. Big Data Analytics Aggregated data generated by equipment-bound sensors can differ from the data found in traditional datasets and processed by analytical methods. Traditional analysis focuses on static data and historical trends but is less effective with high-volume, real-time data. Data veracity is vital to transforming data into usable information; big datasets have a huge pool of data to offset outliers and reduce human error during analysis. Big data frameworks like open-sourced Hadoop and…
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