Remove unwanted parts from strings in Dataframe

I am looking for an efficient way to remove unwanted parts from strings in a DataFrame column.

My dataframe:

     Passengers

1    Sally Muller, President, Mark Smith, Vicepresident, John Doe, Chief of Staff
2    Sally Muller, President, Mark Smith, Vicepresident
3    Sally Muller, President, Mark Smith, Vicepresident, John Doe, Chief of Staff
4    Mark Smith, Vicepresident, John Doe, Chief of Staff, Peter Parker, Special Effects
5    Sally Muller, President, John Doe, Chief of Staff, Peter Parker, Special Effects, Lydia Johnson, Vice Chief of Staff
...

desired form of df:

     Passengers

1    Sally Muller, Mark Smith, John Doe
2    Sally Muller, Mark Smith
3    Sally Muller, Mark Smith, John Doe
4    Mark Smith, John Doe, Peter Parker
5    Sally Muller, John Doe, Peter Parker, Lydia Johnson
...

Up to now I did it with endless handmade copy/paste regex list:

df = df.replace(r'President,','', regex=True) 
df = df.replace(r'Vicepresident,','', regex=True) 
df = df.replace(r'Chief of Staff,','', regex=True) 
df = df.replace(r'Special Effects,','', regex=True) 
df = df.replace(r'Vice Chief of Staff,','', regex=True) 
...

Is there a more comfortable way to do this?

>Solution :

This is one case where apply is actually faster that explode:

df2 = df['Passengers'].apply(lambda x: ', '.join(x.split(', ')[::2])) #.to_frame() # if dataframe needed

output:

                                          Passengers
0                 Sally Muller, Mark Smith, John Doe
1                           Sally Muller, Mark Smith
2                 Sally Muller, Mark Smith, John Doe
3                 Mark Smith, John Doe, Peter Parker
4  Sally Muller, John Doe, Peter Parker, Lydia Jo...