Physicochemical software connection
ACD/Labs and Pharma Algorithms join forces to strengthen in silico screening and prediction
TORONTO—Advanced Chemistry Development Inc. and Pharma Algorithms Inc. are teaming up to pool their software development and business resources to offer in silico screening and prediction.
According to Daria Thorp, president of ACD/Labs, the partnership will enable the companies to better serve the chemical, environmental and pharmaceutical markets, with a focus on in silico physicochemical, ADME, Metabolism and toxicology screening and prediction. She adds the companies' customers will benefit immediately from this merger of technologies and scientific expertise within the two companies.
Both companies are privately owned, and Thorp adds that the details of the agreement are not being made public.
"Immediately, as a result of this merger, our customers will gain access to both sets of complementary models, which to computational chemistry in particular, is a substantial benefit," notes Thorp. "There will be no impact on either people or facilities, aside from the opportunities for enriching partnerships, and the new energy that such integration brings. ACD/Labs is taking on the role of the business provider for the joint product lines, while Pharma Algorithms will continue to contribute significantly to the future product development and integration."
Thorp adds that the companies have a common history. Pharma Algorithms was established by one of ACD/Labs' founders who worked with ACD/Labs for a number of years, and contributed to the methodology and design of some of ACD/Labs most successful products. Both companies were working on a similar line of products and Thorp says it quickly became evident that the existing products could complement each other on both business and technology levels.
"Within the last six months, management of both companies got together to honestly evaluate their respective businesses and uncovered a tremendous amount of synergy," says Thorp. "We discovered that each company has a number of complementary needs that can be easily fulfilled by the other partner and that became the business drive for future integration. My personal feeling from the meetings was that the development teams of both companies, reacting to the requests from their respective customers and scientific communities, have arrived at a very close vision of the market need and how the software can help researcher."
"We are excited to build on the synergy between the companies to create new integrated capabilities, and expand them to a broader range of applications and customers in both chemical and pharmaceutical research and development," adds Pranas Japertas, director of product development of Pharma Algorithms. "We will work on improving our predictions, and developing new models, as well as augmenting the products already in development."
Until a full integration of products is complete, existing maintenance users of both companies will have access, through their current software package, to the corresponding physicochemical prediction product from the other manufacturer.
The entire Pharma Algorithms product line—including modeling software for ADME, Toxicology, DMSO Solubility, and other products—will be available as part of ACD/Labs' product portfolio exclusively through ACD/Labs' extensive international sales and distribution network.
The deal also is a continuation of ACD/Labs' work over the last 15 years to augment its in silico molecular property predictors for properties such as pKa, logD, logP, boiling point, solubility and more.
"The majority of pharma and biotech companies have tested and adopted these products as their corporate standard in computational chemistry, HTS and lead evaluation," says Thorp. "Pharma Algorithms has entered this field relatively recently, but introduced new models and innovative approach to model training with customer's experimental data."
According to Thorp, since software models base their results on available experimental data, the application of the existing models to fundamentally novel chemical classes (which is most often the case in pharmaceutical R&D) requires thorough testing to assess its level of accuracy and therefore having access to more than one model is certainly an advantage.
"Many ADME and tox properties depend on the prediction of the fundamental physicochemical properties mentioned above, and so immediately our users will be able to use both sets of predictive models to obtain values for these physicochemical characteristics, through the initial integration between the software packages made available by both teams within the last two months," Thorp says.
According to Daria Thorp, president of ACD/Labs, the partnership will enable the companies to better serve the chemical, environmental and pharmaceutical markets, with a focus on in silico physicochemical, ADME, Metabolism and toxicology screening and prediction. She adds the companies' customers will benefit immediately from this merger of technologies and scientific expertise within the two companies.
Both companies are privately owned, and Thorp adds that the details of the agreement are not being made public.
"Immediately, as a result of this merger, our customers will gain access to both sets of complementary models, which to computational chemistry in particular, is a substantial benefit," notes Thorp. "There will be no impact on either people or facilities, aside from the opportunities for enriching partnerships, and the new energy that such integration brings. ACD/Labs is taking on the role of the business provider for the joint product lines, while Pharma Algorithms will continue to contribute significantly to the future product development and integration."
Thorp adds that the companies have a common history. Pharma Algorithms was established by one of ACD/Labs' founders who worked with ACD/Labs for a number of years, and contributed to the methodology and design of some of ACD/Labs most successful products. Both companies were working on a similar line of products and Thorp says it quickly became evident that the existing products could complement each other on both business and technology levels.
"Within the last six months, management of both companies got together to honestly evaluate their respective businesses and uncovered a tremendous amount of synergy," says Thorp. "We discovered that each company has a number of complementary needs that can be easily fulfilled by the other partner and that became the business drive for future integration. My personal feeling from the meetings was that the development teams of both companies, reacting to the requests from their respective customers and scientific communities, have arrived at a very close vision of the market need and how the software can help researcher."
"We are excited to build on the synergy between the companies to create new integrated capabilities, and expand them to a broader range of applications and customers in both chemical and pharmaceutical research and development," adds Pranas Japertas, director of product development of Pharma Algorithms. "We will work on improving our predictions, and developing new models, as well as augmenting the products already in development."
Until a full integration of products is complete, existing maintenance users of both companies will have access, through their current software package, to the corresponding physicochemical prediction product from the other manufacturer.
The entire Pharma Algorithms product line—including modeling software for ADME, Toxicology, DMSO Solubility, and other products—will be available as part of ACD/Labs' product portfolio exclusively through ACD/Labs' extensive international sales and distribution network.
The deal also is a continuation of ACD/Labs' work over the last 15 years to augment its in silico molecular property predictors for properties such as pKa, logD, logP, boiling point, solubility and more.
"The majority of pharma and biotech companies have tested and adopted these products as their corporate standard in computational chemistry, HTS and lead evaluation," says Thorp. "Pharma Algorithms has entered this field relatively recently, but introduced new models and innovative approach to model training with customer's experimental data."
According to Thorp, since software models base their results on available experimental data, the application of the existing models to fundamentally novel chemical classes (which is most often the case in pharmaceutical R&D) requires thorough testing to assess its level of accuracy and therefore having access to more than one model is certainly an advantage.
"Many ADME and tox properties depend on the prediction of the fundamental physicochemical properties mentioned above, and so immediately our users will be able to use both sets of predictive models to obtain values for these physicochemical characteristics, through the initial integration between the software packages made available by both teams within the last two months," Thorp says.
