I have tried a different variety of solution with a similar data load -over 1B- but the better that I have found is this:

From MySQL documentation

With some extra work, it is possible to make LOAD DATA INFILE run even faster for a MyISAM table when the table has many indexes. Use the following procedure:

1. Execute a FLUSH TABLES statement or a mysqladmin flush-tables command.

2. Use myisamchk --keys-used=0 -rq /path/to/db/tbl_name to remove all use of indexes for the table.

3. Insert data into the table with LOAD DATA INFILE. This does not update any indexes and therefore is very fast.

4. Re-create the indexes with myisamchk -rq /path/to/db/tbl_name. This creates the index tree in memory before writing it to disk, which is much faster that updating the index during LOAD DATA INFILE because it avoids lots of disk seeks. The resulting index tree is also perfectly balanced.

5. Execute a FLUSH TABLES statement or a mysqladmin flush-tables command.

LOAD DATA INFILE performs the preceding optimization automatically if the MyISAM table into which you insert data is empty. The main difference between automatic optimization and using the procedure explicitly is that you can let myisamchk allocate much more temporary memory for the index creation than you might want the server to allocate for index re-creation when it executes the LOAD DATA INFILE statement.

In order to obtain better performance from the myisamchk you have to tune some params like :

--key_buffer_size --myisam_sort_buffer_size --read_buffer_size --write_buffer_size

Depending on your hardware architecture

Note

When using LOCAL with LOAD DATA, a copy of the file is created in the server's temporary directory. This is not the directory determined by the value of tmpdir or slave_load_tmpdir, but rather the operating system's temporary directory, and is not configurable in the MySQL Server.

So, you you have this kind of problem and your file it's a csv, you can split you "huge" file into chunks

$ split -l (numbersofrowsinfile / ((filesize/tmpsize) + 1)) /path/to/your/<file>.csv

Then repeat your LOAD DATA LOCAL (step 3) for every chunk file.

I hate the checking permissions issue.

You may have to disable key checks before the DROP DATABASE

SET unique_checks = 0;
SET foreign_key_checks = 0;
SET GLOBAL innodb_stats_on_metadata = 0;
DROP DATABASE db_madeintouch;
SET GLOBAL innodb_stats_on_metadata = 1;
SET foreign_key_checks = 1;
SET unique_checks = 1;

UPDATE 2013-04-15 18:04 EDT

I just noticed you have innodb_file_per_table OFF. What gives ?

• You currently have all the InnoDB data and the corresponding index sitting in a single file.
• Any CREATE TABLE statement must make data dictionary updates and look for space (small but annoying in this instance)
• Internal Fragmentation of ibdata1
• Dropping a table means scanning the table and its indexes for availability to lock. With data and index pages possibly fragmented, this takes spindles, seek time, and latency.
• See Pictorial Representation of ibdata1 to see everything that goes into ibdata1

Recommendation : Remove all Data and Index Pages from ibdata1

This will give ibdata1 a breather to handle just data dictionary and MVCC management. In addition, ibdata1 will stay rather lean and mean and can be read more quickly.

You will need to perform the InnoDB Infrastructure Cleanup. I wrote out all the steps back on October 29, 2010 in StackOverflow.

UPDATE 2013-04-22 08:10 EDT

Three suggestions

SUGGESTION 1 : I just noticed something else. You are using an ancient version of MySQL (5.0.45). You should think about upgrading to MySQL 5.6.11 as it performs significantly faster that MySQL 5.5 and way faster than MySQL 5.0.

SUGGESTION 2 : You should also go ahead and implement the InnoDB Infrastructure Cleanup.

SUGGESTION 3 : You should also check the disk itself. If the data is sitting on a RAID10 set, one of the disks may have an issues. Check the disk controller's battery as well because it can slow down disk caching and affect read performance.