The concept of 'if, then' is the backbone of logical reasoning, a simple yet profound structure that mirrors the cause and effect our lives are built upon. Imagine it as a magical doorway in the realm of thought: if you step through one side with a condition, then you emerge on the other with a consequence. This binary dance of conditions and outcomes shapes our daily decisions, from the mundane - "If it's raining, then I'll take an umbrella" - to the monumental - "If I invest in this venture, then I might change the course of my future." 'If, then' doesn't just dictate actions; it's also the pulse of scientific discovery, where hypotheses lead to experiments, which in turn lead to conclusions. In programming, it's the conditional statement that breathes life into algorithms, making computers behave almost like they possess the foresight of a chess grandmaster. It's a testament to human ingenuity, a tool so simple, yet so powerful, that it can map out the complexities of human logic, predict weather patterns, or even navigate the stars.

On the other, less magical, hand, it’s a clue as to how we might limit our imaginations. Pharma tends to operate as a linear calculator, and will do a good enough job at a ‘then’ when presented with an ‘if’ - “if we launch this molecule in 2030, then we’ll generate x revenue… if we are to launch this molecule in this market in 2030, then we need to do y to get it there…” The linearity is logical, and important. But, if each ‘if’ has its own ‘then’ (or, multiple ‘thens’ based on who you give it to…), shouldn’t we be focusing harder on the quality and quantity of our ‘ifs’?

Recognising that small differences in the ‘if’ will lead to big differences in the consequences should lead to a conclusion that we’ll explore a portfolio of ‘ifs’ - in our case, that means a portfolio of target opportunities for our molecule. The IDEA approach focuses on a wide range of potential launch and lifecycle - the ‘then’ for each ‘if’ might be more or less attractive to different stakeholders. When we’re asked for ‘a forecast’ for a molecule, the answer has to be ‘it depends’ - it depends how and where we launch it.

The TPP is an ‘if’, and the traditional pharma model is to ‘then’ the life out of it. This is the source of most of our problems - overanalysis of a hastily chosen profile. Recognising we want a different ‘then’ (or at least we’re interested in a different ‘then’) should lead to a demand for a new ‘if’ - a different TPP, designing with the end in mind. Our linear calculator will give a reliably wrong answer if we continue to feed it the wrong inputs. We might make different decisions about what to take forward once we take account of how to profile the molecule in early phase.