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Welcome to PharmaKarma – my personal site on everything and anything relating to data mining, drug design,  and a bit of pharma industry – all from the perspective of “@home”.  In addition, the premise is that pharma synthetic medication, from the dedicated scientists – but also “karma” – perspective, wants to and can do good.

Karma – means action, work or deed – it also refers to the spiritual principle of cause and effect where intent and actions of an individual (cause) influence the future of that individual (effect). Good intent and good deed contribute to good karma and future happiness (see e.g. Wikipedia). This is were many hard-working scientist come in – even you, the reader, who can perform own research (to a certain extent) from the comfort of home and thus add to a positive reputation of (future) medications!

Be it with the help of myself and consulting to you, or if you want to try/do it yourself – data mining has tremendous possibilities for doing it even for free and with simple tools available from your home!

The blog section these days is updated only occasionally, but it is still well and alive!

“Covid” edit: Certainly the recent pandemic has done for better or worse it part where remote work from home has become acceptable. And thus rendering the need for easily implementable methods as highly important. 

Data Mining

Data Mining

This section is all about  data-mining. With data in this context I am referring to chemical structures and associated data from (mainly) public databases. In general I use the workflow creator “Knime” and combine it as required with Java, SQL and different APIs. See here for more details.



About myself

My name is Alexander Minidis, Ph.D. in organic chemistry, with a specialty in medicinal chemistry and a burning interest in data mining and linking IT with research. That, and working in general cross-functionally is something I found most intriguing in my working life so far. Lately, the hype around AI hasn’t gone past me either!

I studied (organic) chemistry in Basel, Switzerland and did my Ph.D with Professor Andreas Pfaltz in Basel and continued at the Max-Planck-Institute (MPI) f. Kohlenforschung in Mülheim, Germany. After a Post-Doc with Prof. Donna Blackmond at the MPI followed by a Post-Doc with  Prof. Jan Bäckvall in Stockholm, Sweden, I started my industry career at the chemistry CRO Syntagon, Södertälje (Sweden). Missing research, I went to AstraZeneca R&D and became a medicinal chemist. There I continued working as team- and project leader. Over the years I had the opportunity to “dabble” in all sorts of activities, be it synthesis in the lab, data-mining, designing new molecules, writing patent applications, due diligence of new projects or CROs. This, combined with my latter experience, gives me a rather unique background of someone who was worked actively (not only by reading or collaboration) with nearly all aspects of pre-clinical drug research.

After the closure of AstraZeneca research unit two companions and I founded a start-up, Evomedicon AB, a company within drug research and project management. One of the things we were working with was the experience we garnered from our AZ time where we implement lean into research. Interesting to note is, that lean and scrum were (still is) disliked by many researchers, though if you simply take away the naming, one will notice that for efficient workflows lean is more or less already in place. Thus, if adapted specifically for research, lean and scrum can work! Anyway, after 2 years we decided though to close the company and follow other avenues. I continued with research at the Karolinska Institute for some years, using my industry background in an academic setting in the group of Prof. Taipale. Though I required a lot of new know-how regarding biochemical methodologies unknown to me as chemist, the thing required most was data-mining and even programming.

This lead me to support Chemnotia AB in their request to develop a software for analysis of chemical synthesis pathways of larger proteins, an ideal scenario for acting as interface as both, software person and researcher in the same person and in collaboration with the customers.

Shortly after this, I joined Collaborative Drug Design (CDD) as sort of a technical expert for the European “time-zone”, supporting internal and external customers with the main product, CDD Vault, an online database for pharmaceutical drug development. The job included a wide variety of tasks, all from writing knowledgebase articles, tutorial videos, demo-ing the software and setting it up for customers, as well handling enhancement requests, bug-hunting, or giving presentations at conferences.

After an offer by Medivir AB, I worked for a short period as application scientist & data-analyst, supporting researchers with new implementations as well as support for existing software systems – until Medivir announced closure of their R&D portion just two months into this new position. Not waiting what will happen there next, I applied and was recruited by RISE AB, Process and Development where I am working as Chemist/Project Leader. There I am working on development and potential implementation of reaction prediction methods.

Finally, I have done some occasional consulting work, two of the main customers are Awametox and Chemnotia, whom I support(ed) with QA work or data-mining/programming. This concept of being able to support others from home has evolved into this website!

Further details regarding my CV can be found on my LinkedIn profile.

My GitHub repo isn’t that large, but has a few data/chemistry related repos.

Disclaimer: The topics & opinions on this web page are my own and are not representative of any of the companies mentioned here, nor of any of my former employers. This blog and website is independent of PharmaKarma-Consulting (despite being the same physical person behind the consulting part).


No big deal? Dual use of artificial-intelligence-powered drug discovery

A few months ago a paper was published discussing the abuse potential of modern AI based drug models and how it could lead to deliberately ill intended toxic compounds. The article itself can be found here: Dual use of artificial-intelligence-powered drug discovery | Nature (unfortunately behind a pay-wall). I didn’t participate at the conference from …

Curation of yield in the public USPTO reaction datasets – now on Figshare

After getting annoyed of myself and re-curating datasets I already had previously curated, I started with an obvious, simple, but imho important curation of the USPTO reaction datasets which have been “pre-curated” in the past into csv / rsmi format. I collected them and uploaded them here at figshare. The public curation of the USPTO …


Some links of interest with regards to design & mining @home (non-exhaustive list):

Distributed/Volunteer Computing

Other Blogs: