Appreciate this article summarizing points I made re: #diversity in biotech & VC from a panel at the BioPharm America Digital Conference. Key ideas: 1) use recruiters & not just word of mouth to access a more diverse group of candidates; 2) anonymize case studies & if...1/7
...possible, even candidate names on the initial resume review (studies show the same resume with a minority name on it will produce fewer interview offers than a white-sounding name, & that ppl tend to judge the same piece of work more harshly if they believe it was...2/7
...written by a minority or a woman than if they believe it was written by a white male); 3) expand network to meet ppl earlier in their careers & shift searches to ppl a bit younger when possible - in an industry in which diverse professionals are underrepresented at the...3/7
...highest levels, by definition a more sr. pool of candidates is less diverse (hiring more jr. ppl requires more focus on training & mentoring, but these also promote inclusion, belonging, & retention); 4) think critically about the criteria on which professionals (and...4/7
...potential investments) are judged & try to make these consistent. E.g., ask the same types of questions in every interview. Look at the same metrics for judging companies. In review processes, look to see if multiple ppl have the same "growth areas" or strengths - is the...5/7
...underrepresented professional being treated similarly to how a white male is or was treated? Studies show women & those from underrepresented groups have to do more, over & over, to get the same credit as a white male. E.g., women & minorities are promoted based on...6/7
...success, while white males are promoted based on potential; 5) educate your workforce on implicit bias & inclusive leadership; 6) make space for conversations around different experiences team members have had to foster understanding & build awareness. 7/7
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When I saw this headline, I feared the article would be reductionist and coy. But the authors hit on many of the right points: 1) individuals’ political beliefs don’t solely (or even mostly) relate to potential impact on the industry in which they... 1/7 statnews.com/2020/10/30/is-…
...work; 2) Trump’s deep-seated antipathy to science is an affront to drug developers; 3) Trump’s politicization of the drug dev’t process & undermining of the FDA & CMC threaten our industry; 4) Trump may not raise the corp tax rate or seek campaign finance reform, but...2/7
...his approach to the drug industry has been hostile, unpredictable, & uninformed by dialogue. The article doesn’t note Trump’s desire to dismantle ObamaCare, which would have a negative impact on many ppl’s health as well as the biopharma industry. It also doesn’t mention...3/7
Thread for folks looking for roles in biopharma VC. Nearly every week I speak to someone who wants to get into biopharma VC. One high-level theme: even for entry roles, you *generally* need to check the box “understands science” as well as the box “can do basic financial... 1/9
...modeling”. Often ppl who reach out to me have substantial scientific creds but don’t have any finance experience. That’s not a deal killer for every firm or role – with a very strong scientific background and some other form of business training (non-finance business...2/9
...roles, MBA or relevant undergrad major, even being self-taught) many people can do just fine in biopharma VC (I wouldn’t try to do healthcare services VC/PE, though, unless you’re a whiz at financial modeling). Others may enter the industry from an entrepreneurial /... 3/9
Thread: advice for preclinical biotechs on their in vivo datasets. For preclinical biotechs seeking funding, the difference between a vaguely interesting data set & a fundable data set often comes down to 1) controls used (especially positive controls); 2) dose range tested. 1/7
...We see so many companies fail to utilize obvious positive controls (which is to say, ones that provide some way to contextualize the data with the co’s molecule vs. other experiments done in the field). Why is this? Maybe to save money or time? Or perhaps because it’s...2/7
...viewed as sufficient to show some signal, and risky to have a comparator? Producing data at only a single dose (especially a really high one) is also in many ways a waste of the experiment. It’s critical to design your experiments with these things in mind, even if... 3/7