complex Difference-in-difference formula

I have 5-year sales information from a grocery store in Canada. I want to check whether an event that happened in 2017, affected the effect of the price of a product on its sales.

For example, imagine that before treatment price elasticity (i.e. the degree to which changes in price impact the unit sales of a product) for diary goods was -0.05, I am eager to know whether my treatment changed it or not. Actually, I already know that price influences sales, but I suspect that the imposition of the treatment might alter the consumers’ price sensitivity.

The standard DiD model only investigates the impact of treatment on the outcome variable. While I need to see whether the treatment has affected the coefficient of the regression model (Sales ~ Price) or not. In other words, I need to check whether the treatment affected the relationship between my independent variable (Price) and dependent variable (Sales). Would you please guide me on what formula should I use as the standard difference-in-difference model does not seem to be working here?

$$
log(Outcome_{it})= beta_1 + beta_2Treat_{i} + beta_3 Post_{t} + beta_4 (Treat times Post)_{it} + epsilon_{it}
$$

can I use the below model instead?

$$
log(Sales_{it})= beta_1 + beta_2Treat_{i} times Price_{it} + beta_3 Post_{t} times Price_{i} + beta_4 DiD_{it} times Price_{it} + epsilon_{it}
$$

where DiD is:

$$
DiD = Treat times Post
$$