How do I get budget approval for drug discovery software?
Buying software for your company can be a challenge. Every organisation does things differently, and there is often no handbook…
Interested in how StarDrop can enhance your research? Our step-by-step guide will get you set up for a successful evaluation, so you can start transforming your discovery. Optibrium offers an easy way to evaluate our molecular discovery software through a cloud-based solution, allowing you to access StarDrop from anywhere with no installation required.
1. Speak with your Optibrium representative
To tailor the evaluation to your needs, we’ll need some key information:
- Which modules? Which StarDrop modules are you particularly interested in? Each module offers unique capabilities for solving complex research problems. Check out StarDrop’s page to learn more about the different modules within StarDrop.
- Trial objectives: What are your goals during the trial period? Defining these upfront ensures we can help you achieve meaningful outcomes.
Not sure where to start? Here are some themes that our evaluators tend to focus on:
- Is it intuitive and simple to use?
- Are the predictions close to what we saw experimentally?
- Does it have the critical functionality we need?
- Will it integrate with our existing research infrastructure?
- Will it improve communication and collaboration between users and teams?
2. Form your evaluation team
Who will be part of the trial? Collaborating with the right team members, including those who will use the software day-to-day and key decision makers such as budget holders, ensures you can fully explore how StarDrop fits your research needs and will benefit your organisation:
- Research teams: Which members of your research teams will participate in the evaluation?
- Challenges to solve: What specific research problems do they need to address using StarDrop?
- Success criteria: How will you measure the success of the evaluation? Establishing clear criteria helps guide the trial and assess the impact of StarDrop on your workflows.
3. Schedule your evaluation
Our evaluations usually last for two weeks, during which you will taste of the benefits of StarDrop and relevant modules, to make a definitive decision around what set up will work best for your team. The evaluations include:
- Start date: A kick-off meeting with hands-on training (approximately 2 hours). Our team will ensure that you and your evaluation team are fully trained on StarDrop’s key features, enabling you to hit the ground running.
- Mid-evaluation check-in: A chance to review progress and adjust to ensure you get the most out of your time investment.
- Follow-up meeting: A final discussion to review outcomes and next steps.
4. Get set up for success
Once your evaluation dates are confirmed, each user will receive login credentials to access StarDrop through our cloud-based platform. You’ll also have access to our expert-led training, ensuring your team is fully equipped to make the most of the trial period.
Throughout your evaluation, you’ll have full access to our industry-leading Application Science team, ensuring you get the most out of StarDrop and can tackle any questions or challenges that arise.
5. Make a decision
While we run evaluations every day, we know you don’t! So, to help, we have created a simple step-by-step guide that will support you to get the most out of your two weeks. It will ensure you touch on the key aspects of our software and make you feel confident that you are making the right decision. We are happy to share this with you before we start the evaluation; just ask!
Ready to transform to data-driven decision making and trial StarDrop?
Simply complete the form now for a free personalised demo and see how StarDrop fits your unique research needs.
Keen to find what factors will impact the cost of StarDrop?
Our CCO, James Halle, talks about key considerations when budgeting for drug discovery software.
About the author
Tamsin Mansley, PhD
President, Optibrium Inc. and Global Head of Application Science
Tamsin holds a PhD in Organic Chemistry from University of East Anglia in the UK and pursued Postdoctoral studies in the labs of Prof. Philip Magnus at University of Texas, Austin.
She is an experienced drug discovery scientist, having worked as a medicinal chemist at Eli Lilly and UCB Research. Her interests lie in coupling machine learning and artificial intelligence techniques with generative chemistry approaches to explore chemistry space and guide compound design.
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