Posted to MedZilla on 8/25/2019

Takeda Pharmaceuticals

US-MA, Computational Chemist, Discovery Toxicology R0005760-MZ


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Job Description


  • Apply bio/cheminformatic techniques and execute cutting edge algorithmic solutions to enable the mining, curation, analysis and modeling of complex biological and pharmacokinetic data
  • Directly support both small and large molecule project teams to enable superior candidate selection through structure- and pharmacology-based analyses of in vitro and in vivo toxicological data
  • Work collaboratively with Discovery Toxicology colleagues to assist in the development and validation of novel in silico and in vitro predictive tools for the prediction of adverse toxicological events


  • Promote superior lead optimization and clinical candidate selection through integration into early discovery project teams and supporting the application of Takeda s Early Safety Strategy
  • To be proactive in the assessment, mitigation and timely dissemination of a project s potential safety risks
  • Use existing and novel bio/cheminformatic tools and techniques, including systems pharmacology, to extract and visualize knowledge from chemical, biological and pharmacological data.
  • Work with Discovery Toxicology and Pharmacology scientists to develop tools, algorithms and databases, for the advancement of Takeda s biologics strategy.
  • Influence the direction of drug design and improve the quality of drug candidates through the development of toxicology-based SARs
  • Create structure-based relational databases to aid in the interrogation, interpretation, and visualization of biological, pharmacokinetic, and toxicological data.
  • Work collaboratively on computational projects across multiple disciplinary areas, including drug safety, DMPK, medicinal chemistry, and pharmacology
  • Develop and maintain global platforms that integrate internal and external toxicity prediction models and databases


  • PhD in computational chemistry or equivalent with demonstrable understanding of medicinal and organic chemistry
  • Passion to decrease safety related attrition in pharmaceutical drug projects
  • Demonstrated experience in data curation, data mining and an ability to interrogate, interpret, and visualize large and diverse, biological and toxicological datasets
  • Demonstrated understanding of all aspects of drug discovery including medicinal chemistry and basic principles of drug pharmacokinetics and metabolism.
  • Demonstrated experience with linear and non-linear statistical modeling methodologies for machine learning
  • Demonstrated experience in leveraging in silico methodologies to drive drug discovery projects
  • Demonstrated ability in the validation of new models and databases
  • Experience with programming and scripting languages (e.g. Perl, C/C++, Java, R, Python) along with experience of data manipulation tools such as Pipeline Pilot and Spotfire
  • Demonstrated experience and ability to work effectively in a matrix, global environment as part of a multidisciplinary team is essential.
  • Pre-clinical or clinical drug safety experience is desirable
  • Experience with computational biology tools and identifying pharmacological pathways of relevance to toxicology is desirable
  • Demonstrated ability to independently implement computational workflows starting from raw data through processing, analysis, and visualization
  • Skilled in clearly and concisely communicating complex computational approaches and methodology to non-computational scientists and other stakeholders
  • Strong, written, oral communication and influencing skills are essential
  • Self-starter with a high level of independence

401(k) with company match and Annual Retirement Contribution Plan
Tuition reimbursement
Company match of charitable contributions
Health & Wellness programs including onsite flu shots and health screenings
Generous time off for vacation and the option to purchase additional vacation days
Community Outreach Programs
Empowering Our People to Shine
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Boston, MA

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Full time

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