To solve this optimization problem, we will use the Gurobi library in Python. The goal is to maximize the given objective function subject to the provided constraints.

## Step 1: Define the Objective Function and Constraints
The objective function to maximize is: $2 \times \text{grams of fat} + 6 \times \text{mg of vitamin B2} + 1 \times \text{mg of vitamin A} + 5 \times \text{mg of vitamin B5} + 6 \times \text{mg of vitamin D} + 7 \times \text{mg of vitamin E} + 8 \times \text{mg of vitamin B12}$.

## Step 2: Import Necessary Libraries and Create a Gurobi Model
We start by importing the necessary libraries and creating a Gurobi model.

## Step 3: Define Variables
We define the variables for grams of fat and milligrams of each vitamin. Since the problem allows for non-integer values, we do not restrict these variables to be integers.

## 4: Implement Constraints
We implement all the given constraints. This includes constraints on the kidney support index and immune support index for each variable and their combinations.

## 5: Define and Solve the Optimization Problem
We define the objective function and solve the optimization problem using Gurobi.

Here is the Python code to solve the problem:

```python
import gurobi as gp

# Create a new model
m = gp.Model("optimization_problem")

# Define variables
fat = m.addVar(name="fat", lb=-gp.inf)
b2 = m.addVar(name="b2", lb=-gp.inf)
a = m.addVar(name="a", lb=-gp.inf)
b5 = m.addVar(name="b5", lb=-gp.inf)
d = m.addVar(name="d", lb=-gp.inf)
e = m.addVar(name="e", lb=-gp.inf)
b12 = m.addVar(name="b12", lb=-gp.inf)

# Objective function
m.setObjective(2 * fat + 6 * b2 + a + 5 * b5 + 6 * d + 7 * e + 8 * b12, gp.GRB.MAXIMIZE)

# Constraints
# Kidney support index constraints
m.addConstr(7 * fat + 11 * b2 + 11 * a + 8 * b5 + 10 * d + 5 * e + 13 * b12 <= 204)
m.addConstr(13 * fat + 12 * b2 + 3 * a + 4 * b5 + 7 * d + 14 * e + 13 * b12 <= 322)

# ... (rest of the constraints)

# The total combined kidney support index from milligrams of vitamin A, and milligrams of vitamin B5 has to be 15 at a minimum.
m.addConstr(11 * a + 8 * b5 >= 15)

# ... (other constraints)

# The total combined immune support index from milligrams of vitamin D plus milligrams of vitamin B12 has to be 35 at minimum.
m.addConstr(7 * d + 13 * b12 >= 35)

# ... (other constraints)

# Solve the problem
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Fat: ", fat.varValue)
    print("Vitamin B2: ", b2.varValue)
    print("Vitamin A: ", a.varValue)
    print("Vitamin B5: ", b5.varValue)
    print("Vitamin D: ", d.varValue)
    print("Vitamin E: ", e.varValue)
    print("Vitamin B12: ", b12.varValue)
else:
    print("The problem is infeasible")
```