In a lean drug discovery model, more resources are invested in the early stages of drug discovery (agile and cheap), where computers are used to model biology and chemistry. This allows for better prediction, testing, and learning cycles, and feeding the later development stages (long and expensive), with candidate molecules with higher chances to succeed.
Our methodology that mines an unexploited chemical space, finding starting points with larger chemical diversity, will enable the development of new therapies for unmet medical needs and the research of new treatments. We help companies in Target Identification, Hit-Identification, Hit-to-Lead and Lead Optimization drug discovery stages by finding novel hits, improving ligand binding properties (ADME, Tox, etc.), obtaining insights of ligand/receptor interactions and identifying original backup compounds.
In a lean drug discovery model, more resources are invested in the early stages of drug discovery (agile and cheap), where computers are used to model biology and chemistry. This allows for better prediction, testing, and learning cycles, and feeding the later development stages (long and expensive), with candidate molecules with higher chances to succeed.
Our methodology that mines an unexploited chemical space, finding starting points with larger chemical diversity, will enable the development of new therapies for unmet medical needs and the research of new treatments. We help companies in Target Identification, Hit-Identification, Hit-to-Lead and Lead Optimization drug discovery stages by finding novel hits, improving ligand binding properties (ADME, Tox, etc.), obtaining insights of ligand/receptor interactions and identifying original backup compounds.
Multi-platform software solutions using proprietary algorithms designed to explore a larger and more diverse chemical space.
A field-based virtual screening software package designed to find candidate molecules with larger chemical diversity from proprietary, public or commercial compound libraries.
Unmatched accuracy in exploring ultra-large synthesizable chemical libraries with innovative virtual screening software, fusing AI and QM technologies to uncover novel and diverse hits in uncharted chemical spaces.
A 3D Quantitative Structure-Activity Relationship (QSAR) software package that builds statistical models (CoMFA, CoMSIA and HyPhar) based on data obtained from experimental assays.
A field-based virtual screening software package designed to find candidate molecules with larger chemical diversity from proprietary, public or commercial compound libraries.
State-of-the-art virtual screening software package to accurately screen ultra-large synthesizable chemical libraries, combining AI and QM algorithms to overcome the computational and storage challenges.
A 3D Quantitative Structure-Activity Relationship (QSAR) software package that builds statistical models (CoMFA, CoMSIA and HyPhar) based on data obtained from experimental assays.
Our cross-disciplinary and experienced team of medicinal & computational chemists, bioinformaticians, pharmacists, and engineers provides outstanding results using our superior and proprietary benchmarked technology.
Every discovery project, from Target-to-Hit, Hit-to-Lead (H2L) and Lead Optimization (LO), sees our in-silico capabilities applied in a unique and tailor-made way. Individual tasks with independent Go/No-Go decisions ensure the de-risking of our customer’s projects. In conjunction with our superior, proprietary and benchmarked technology, the flexibility to match your needs will give your drug discovery project the boost you envision.
Pharmacelera provides computational chemistry services to:
SMALL BIOTECH COMPANIES | BIG PHARMA R+D DPT. | PUBLIC RESEARCH INSTITUTIONS | PUBLIC PROVIDERS (CROs)
Our cross-disciplinary and experienced team of medicinal & computational chemists, bioinformaticians, pharmacists, and engineers provides outstanding results using our superior and proprietary benchmarked technology.
Every discovery project, from Target-to-Hit, Hit-to-Lead (H2L) and Lead Optimization (LO), sees our in-silico capabilities applied in a unique and tailor-made way. Individual tasks with independent Go/No-Go decisions ensure the de-risking of our customer’s projects. In conjunction with our superior, proprietary and benchmarked technology, the flexibility to match your needs will give your drug discovery project the boost you envision.
Pharmacelera provides computational chemistry services to:
SMALL BIOTECH COMPANIES | BIG PHARMA R+D DPT. | PUBLIC RESEARCH INSTITUTIONS | PUBLIC PROVIDERS (CROs).
Science is encoded in the DNA of Pharmacelera. Computational and medicinal chemistry, machine learning and artificial intelligence, quantum mechanics and high performance computing are some of the multiple skills of our team. Our solutions and services range from the search of new ideas for your medicinal chemistry teams or new chemical and synthesizable matter, to the use of precise descriptors applicable to predicting pharmacological properties using machine learning.
Science is encoded in the DNA of Pharmacelera. Computational and medicinal chemistry, machine learning and artificial intelligence, quantum mechanics and high performance computing are some of the multiple skills of our team. Our solutions and services range from the search of new ideas for your medicinal chemistry teams or new chemical and synthesizable matter, to the use of precise descriptors applicable to predicting pharmacological properties using machine learning.
We believe that collaborations are the appropriate mechanism to build solutions with greater impact. Hence, we are a company that is always looking for win-win collaborations and partnerships with organizations that share our mission and values.
Please get in touch and our team of experts will answer all your questions.
