Con esta herramienta te facilitamos un acceso a todas las ofertas y demandas de tecnología europeas y a búsquedas de socios para participar en propuestas europeas de I+D publicadas en la red Enterprise Europe Network, pudiendo filtrar los resultados para facilitar las búsquedas más acordes con tus necesidades.

¿Quieres recibir estos listados de oportunidades de colaboración en tu correo de forma periódica y personalizada? Date de alta en nuestro Boletín

Para optimizar los resultados de la búsqueda, se recomienda utilizar términos en inglés.

Pyme sueca ofrece una metodología computacional única para la predicción virtual del metabolismo y farmacocinética clínica humana

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOSE20190819001
Publicado:
17/10/2019
Caducidad:
17/10/2020
Resumen:
Una pyme sueca del sector de tecnologías farmacéuticas ha desarrollado una plataforma validada basada en datos clínicos humanos para predicciones de ADME/PK (absorción, distribución, metabolismo, excreción, farmacocinética) de medicamentos y candidatos directamente a partir de la estructura química. Esta plataforma permite llevar a cabo análisis predictivos en productos farmacéuticos, cosméticos y toxicología. La metodología computacional (in silico), basada en algoritmos y una base de datos única, aprendizaje automático, inteligencia artificial (IA) y metodología de predicción conformada, ha sido validada interna y externamente y ha demostrado superar los modelos in vitro y animales convencionales en términos de precisión y rango. También se aplica en metabolitos de medicamentos y diversos tipos de productos químicos. La empresa busca compañías farmacéuticas en el área de profármacos, antibióticos y metabolitos de medicamentos con el fin de establecer acuerdos de licencia, así como socios para alcanzar una cooperación técnica y en materia de investigación para desarrollar nuevos modelos y/o nuevas áreas de aplicación, por ejemplo, relacionadas con la toxicología o el desarrollo de cosméticos.

Details

Tittle:
A Swedish SME offers a unique computational methodology for virtual prediction of human clinical pharmacocinetics and metabolism
Summary:
A Swedish pharmatech SME has developed a validated platform based on human clinical data for predictions of ADME/PK (Absorption, Distribution, Metabolism, Excretion, PharmacoKinetics) from chemical structure. It enables predictive analytics for pharmaceuticals, cosmetics and toxicology.

The SME seeks partners for licensing for existing models with pharmaceuticals as well as technical or research cooperation agreements for new models or new application areas in Europe, Asia and in the US.
Description:
A Swedish SME, active in the area of pharmaceutical technology, has developed a unique platform, including software, for high quality predictions of human clinical ADME/PK (Absorption, Distribution, Metabolism, Excretion, PharmacoKinetics) of drugs and drug candidates directly from chemical structure. This computational (in-silico) methodology, based on unique algorithms and database, machine learning, artificial intelligence (AI) and conformal prediction methodology, has been internally and externally validated and shown to outperform conventional in vitro and animal models in accuracy and range. It is also applicable for drug metabolites and various kinds of chemicals.

Lab methods, such as different human cell systems (in vitro) and animal models, are commonly used for producing prediction of doses and exposures of drug candidates in humans. Good predictions of ADME/PK in humans are essential for setting safe start doses in early clinical trials and for assuring adequate exposure and pharmacological profiles in patients. Prediction methods with poor quality jeopardize successful and cost-efficient drug discovery and development.

Animal-based ADME/PK-methods have been demonstrated to have lower median prediction errors and to cover a significantly broader range of compounds compared to in vitro methods. However, some essential parameters are poorly predicted from animal data and maximum errors are extreme for both animal and in vitro based predictions. In silico tools have been produced by many, often based on in vitro data. These have not reached a prediction accuracy and range as good as for lab methods.

The platform utilizes unique human clinical data (quality-checked and stratified) and algorithms, machine learning, AI and conformal prediction methodology (which gives guaranteed confidence estimates). The predictions outperform lab methods in accuracy and range. The platform, which has more than 50 models, including for uptake from the skin, eyes, lungs and blood-brain barrier, has been extensively validated internally and externally (also by major international pharmaceutical companies).

Recently, the SME also launched new software - a human clinical ADME/PK-studio - with features that enable direct optimization of characteristics of candidate drugs and drugs in a user friendly mode and at an advantageous price.

The SME is looking for partners for licensing agreements with pharmaceutical companies (for example, within the area of prodrugs, antibiotics and drug metabolites) and partners on the basis of technical or research agreement for developing of new models and/or new application areas for example relating to toxicology or cosmetics development.
Advantages and Innovations:
The SME has developed and validated a unique, confidence-assuring, computational methodology that outperforms comparable lab methods - see attachment for an overview.

Advantages include superior accuracy (lower errors), range and compound coverage, completeness and successful external blind validations. The platform outperforms laboratories and other computational methods, also according to external blind validations by major international pharmaceutical companies.

Compared to traditional methods it enables drug developing companies and institutions to:
- significantly reduce or replace animal and in vitro experiments,
- frontload decision-making,
- improve cost-efficiency and productivity, and
- reduce substance synthesis and risks, without losing predictive quality.
Stage of Development:
Already on the market
IPs:
Secret Know-how

Partner sought

Type and Role of Partner Sought:
The SME is looking for partners for licensing agreements with pharmaceutical companies (for example, within the area of prodrugs, antibiotics and drug metabolites) for the models that are already in the platform.

The SME is also interested in partners on the basis of technical or research agreements to develop and validate new models and/or explore new application areas. Current clients are primarily in pharmaceuticals and new applicaiton areas could include partners in chemical industries inthe area of toxicology or partners in cosmetics to explore benefits of the platform to predict uptake of and exposure to cosmetics.

Client

Type and Size of Client:
Industry SME <= 10
Already Engaged in Trans-National Cooperation:
Si
Languages Spoken:
English
Swedish

Dissemination

Restrict dissemination to specific countries:
Denmark, Finland, France, Germany, Italy, Japan, Korea, Republic Of, Norway, Singapore, Spain, Switzerland, United Kingdom, United States

Keywords

Technology Keywords:
03004011 Care, Hygiene, Beauty
03004003 Colorantes y tintes relacionados con ingeniería y tecnología química
06002007 Ensayos in vitro, experimentos
03004007 Pharmaceutics
06002010 Toxicología