The smartest (and easiest) way to identify ideal partners and plan strategic outreach.
We recently used MotionHall to generate target lists of potential licensees for two indications: one where we've been working for several years, and a second that represents a new disease area for business development activities. The lists are amazingly accurate, and in the case of the new indication has saved us a great deal of time and effort in trying to generate the same list using traditional methodologies...
Acorn Partners, an investment bank, took on a promising phase 3 pain asset for out-licensing.
Relying on their long history in the industry, unique relationships and databases, they pieced together nearly 50 potential partners for the deal.
However, when it came time to reach out to potential partners they had trouble advancing conversations or getting to a negotiation.
Committed to closing the deal, they redoubled their efforts and added another 150 companies to their strategic outreach.
Over the next 24 months, Acorn Partners would contact all 200 companies with no success.
With their client running out of cash and no serious competition for the deal, they found a way to cut an unfavorable M&A deal with a European company active in the therapeutic area.
The CEO at the client company was furious.
Acorn Partners later challenged MotionHall's data system to predict the most likely partners for this difficult deal.
MotionHall's OutMatch AI considered thousands of companies around the world and returned 80 matches for the deal, but only 2 of these were strongly ranked matches.
The number one match at a 92% match score was a lesser known European pharma, who turned out to be the final buyer for the deal.
If Acorn Pharma had known that there were only two strong matches for the deal globally, they might have spent their time differently and been more successful.
Ember Biotech joined the MotionHall platform to expand their knowledge of potential M&A buyers for a phase 3 asset treating endocrine tumors.
MotionHall's OutMatch AI considered thousands of companies around the world and returned 52 matches for the deal, introducing 16 new matches Ember Biotech hadn't considered previously.
However, more surprising and also more valuable to Ember was discovering, as in the previous scenario, that only 2 of these were strongly ranked matches.
Ember Biotech responded to this insight by reconsidering their M&A strategy.
If there are only two really strong matches for our deal, they reasoned, then we should know everything about them and play our cards very carefully to get the deal that we want before we run out of money.
Ember Biotech is currently advancing deal conversations and happy with the way this new focused strategy is playing out.